Model fallback and AI pricing strategy are not engineering details. They are product decisions with direct consequences for user trust, retention, and revenue sustainability. Getting them wrong does not just create technical debt; it creates business risk.

This article walks through a five-layer framework derived from real production experience building AI-powered products, covering how intelligent routing, fallback architecture, financial observability, value-based pricing, and guardrails work together as a coherent product and engineering strategy.

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Why most AI products fail before they scale

The gap between a working AI prototype and a reliable production product is wider than most teams expect. Industry data makes this visible: roughly 40% of LLM outputs, according to OptimusAI, are not consistently reliable in production environments, and around 95% of AI pilots, according to Typedef.ai’s study “13 LLM Adoption Statistics”, stall before reaching scale — not because the models underperform, but because the surrounding infrastructure is not designed to sustain real usage conditions.

The root cause is almost always structural. Teams build features that work in isolation but lack the operational layers needed to handle cost variability, model failures, and unpredictable user behavior at scale. When those layers are absent, AI products become expensive to operate, fragile under load, and impossible to price sustainably.

The solution is not a better model. It is a better architecture — one that treats model fallback and pricing as first-class product concerns from day one.

The five-layer framework: from feature to reliable product

The framework below reflects how production AI systems need to be structured when reliability, cost control, and user trust are non-negotiable requirements. Each layer addresses a specific failure mode that appears consistently across AI product development.

“We don’t sell tokens. We sell reliable solutions. The architecture must reflect that.”

Layer 1: Intelligent model routing: the 20x cost problem

The single most impactful architectural decision in an AI product is also the most commonly overlooked: not every task requires the same model.

In practice, cost differences between the cheapest and most expensive commercially available models can reach 20x or more. Using Claude Sonnet 4.5 at $3.00 per million input tokens for every request — including simple summaries, data extractions, and short classifications — when a model at $0.15 per million tokens handles those tasks equally well is not a quality decision. It is a marginal decision made by default, and it is unsustainable.

A well-designed routing layer dynamically assigns each task to the most appropriate model based on complexity, balancing three variables simultaneously: cost, latency, and output quality.

A real-world routing policy looks like this:

• Default model (80% of tasks): A lightweight, fast model handles summarization, extraction, and tool selection for simple interactions and basic Q&A. Cheap, fast, and reliable for well-scoped tasks.
• Premium model (upgrade path): A more capable model is invoked when task complexity crosses a defined threshold — multi-step planning, complex tool orchestration, reasoning-intensive automation workflows.
• Economic fallback: An alternative provider’s model enters when the primary infrastructure fails or when budget thresholds are reached.

Latency compounds the cost argument. Higher-capability models are slower — not marginally, but meaningfully. A user waiting 30+ seconds for a response to a simple request will not stay. They will reload the page, assume the product is broken, and lose confidence. Routing decisions affect both the income statement and the product experience.

At 20x cost variation, intelligent routing is not an optimization. It is a product survival decision.

Layer 2: Model fallback and redundancy: designing for inevitable failure

Rate limits, server errors, and infrastructure outages are not edge cases. They are operational facts for any AI product running in production. The architecture question is not whether failures will happen — it is whether the product recovers automatically and transparently, or exposes failures directly to users.

Most developers design fallbacks like a ladder: if Model A fails, try a slightly better Model A. In a true production environment, this can lead to outages.

A production-grade fallback architecture is not a linear list; it is a matrix. You must solve for two different types of failure simultaneously: loss of service and loss of quality.

• Infrastructure Diversity: This solves for connectivity. If Provider A returns a 5xx or a regional outage occurs, your architecture must immediately jump to an entirely different infrastructure (Provider B or a self-hosted instance).
• Model Tiers: This solves for logic. If the primary model (low-cost) fails to parse a complex prompt or hits a token limit, you escalate to a “Frontier” model (high-capability) to maintain the quality of the output.

A robust system operates on a defined execution order that balances these two pillars, for example:

1. Primary model (default, lowest cost, primary provider)
2. Upgraded model (same provider, higher capability)
3. Legacy model (same provider, maintained for fallback)
4. Cross-provider model (alternative infrastructure, eliminates single point of failure)
5. Last-resort model (emergency fallback, minimal cost)

When a model returns an HTTP 429 (rate limit) or a 5xx server error, the system triggers a Circuit Break pattern. The failing model enters a quarantine window, starting at 10 minutes and utilizing Exponential Backoff in production-grade systems, during which the system automatically routes requests to the next model in the sequence. After the cooldown period, the original model is retested automatically, since many failures are transient.

Critical distinction: not every error type warrants a fallback. When input exceeds a model’s context window, routing to a smaller model will produce the same failure — smaller models have narrower context limits, not wider ones. In these cases, the correct response is a clear user-facing message with a meaningful next step, such as opening a new conversation.

Multi-provider architecture adds a qualitatively different layer of resilience. By distributing across two independent infrastructure providers (for example, AWS Bedrock as primary and Groq as fallback), the system eliminates its single point of failure. If one provider goes down entirely, traffic shifts automatically without any user interruption.

From a product perspective, fallback is also a pricing conversation. When model pricing changes without notice — which LLM providers do regularly — teams without fallback architecture face a binary choice: absorb the cost increase or break the product. Teams with a tested fallback chain can absorb that disruption in minutes.

Layer 3: Financial observability: you cannot price what you cannot measure

One of the most consequential gaps in early-stage AI products is the absence of cost visibility at the operational level. LLM-based systems have dynamic, per-token pricing across multiple models and providers. Without deliberate tracking, costs accumulate invisibly until an invoice makes the problem undeniable.

Financial observability means tracking cost not just per API call, but per operation type — per feature, per workflow, per interaction. Every distinct product action should have its cost attributed individually: chat messages, task planning, tool selection, automation runs, and report generation.

This granularity transforms how product and business decisions get made.

A real consequence of implementing this: When a team enabled operation-level cost tracking on an automation feature, they discovered the feature was costing $4 to 10 per execution — significantly more than the monthly subscription price they had been planning to charge.

Without that data, they would have launched a feature that actively eroded margins. With it, they redesigned the pricing model, shifting from monthly to weekly billing, to align the user-facing price with the actual delivery cost.

What to track per operation:

• Input and output token counts
• Model used and provider
• Operation type and feature context
• Estimated cost per call
• Number of agent turns to complete the task

Infrastructure consideration: reporting queries should not compete with production traffic. A practical implementation logs token usage to a primary operational database (for real-time tracking) while syncing to a dedicated analytics replica on write. This ensures reporting never degrades the user experience.

Prompt caching adds a complementary cost reduction lever. For long, static, frequently repeated prompts — such as those describing available tools, system configurations, or data models — caching can reduce token costs by up to 90% by serving stored results rather than re-invoking the model. This is particularly valuable for automation workflows where the same system context is sent repeatedly across different user sessions.

Financial observability is not just cost control infrastructure. It is the data layer that makes a pricing strategy possible.

Layer 4: AI pricing strategy: charge for value, not for tokens

How an AI product prices externally should reflect how it is structured internally. And the most common structural mistake is pricing based on token consumption.

Token-based pricing has a predictable failure mode: it transfers the complexity and unpredictability of model economics directly to the user. Non-technical audiences — which is most end users — cannot evaluate whether a 2,000-token response represents good value. They do not know what a token is, and they should not need to. Exposing that complexity creates friction, reduces adoption, and misaligns perceived value with actual product utility.

Value-based pricing replaces token consumption with task completion as the billing unit. Users pay for what they receive: outcomes, reports, automations, and summaries.

Real cost data from production systems illustrates the pricing math:

For a task with 2,000 input tokens and 500 output tokens:

• Claude Sonnet 4.5: ~$0.0135 per task
• Claude Haiku 4.5: ~$0.0045 per task (3x cheaper)
• GPT-OSS 120B via Groq: ~$0.0006 per task (22x cheaper)

An automation that runs once per business day, using a premium model, costs approximately $5-10 per execution; $100-200 per month at full usage. That unit economics reality should drive how the feature is packaged and priced before launch, not after users start complaining about unexpected charges.

Practical pricing principles for AI products:

• Price by task, outcome, or workflow completion, not by token count or API call
• Build in a 20-30% cost buffer to absorb model pricing changes without margin erosion
• Review pricing quarterly and whenever a provider updates its rate structure
• When users can select model quality (fast vs. best), communicate the cost difference explicitly at the point of selection
• Consider frequency packaging: weekly billing for high-cost daily automations often converts better than monthly billing at the same total price

The core principle: the price of a feature should reflect the value it delivers — the task resolved, not the cost of the infrastructure that processed it.

Layer 5: Guardrails and trust: where safety becomes product quality

Guardrails are the layer that makes AI products safe to use in production — for users, for the business, and for compliance purposes. They operate in two directions simultaneously.

Input guardrails intercept problematic requests before they reach the model. This includes filtering out PII that should not be sent to external LLM providers, blocking queries outside the product’s defined scope (avoiding unnecessary token spend on out-of-scope requests), and enforcing rate limits at the user and organization level to prevent margin erosion from power users.

Output guardrails validate what the model returns. This means checking for policy violations, inappropriate content, data that should not be surfaced, and brand consistency failures. A guardrail that catches a competitor’s name appearing in a brand’s customer-facing chatbot response is not a minor technical feature — it is reputation protection.

A second model call can serve as an automated self-check: a separate invocation that evaluates response quality and compliance without the context of the original conversation. This LLM-as-a-judge pattern enables scalable quality auditing that would be impossible to do manually at any meaningful volume.

Guardrail telemetry is as important as the guardrails themselves. Teams should track:

• Block rate by reason (safety violations vs. budget limits vs. scope violations)
• False positive rate (legitimate requests incorrectly blocked)
• Context limit hits (users running into conversation length ceilings)
• Data leak incidents

The user-facing side of guardrails matters as much as the technical implementation. When a limit is reached, the product should explain what happened and offer a meaningful alternative — not show a generic error. “You’ve reached the context limit for this conversation. Open a new chat to continue” is a product experience. A blank screen or an unexplained error is a trust problem.

Budget guardrails also create the conditions for transparent pricing. When users understand that each interaction costs a defined number of credits, and when limits are communicated clearly before they are reached, the pricing model feels fair rather than arbitrary.

The performance vs. quality trade-off: what teams rarely discuss honestly

There is a real and unavoidable trade-off in AI model selection that product teams often avoid: higher-quality models are slower, and that slowness is not accidental — it is structural.

When a model enters “thinking mode” — the extended reasoning process that produces higher-quality outputs — it is, by design, taking more time. The quality is inversely proportional to the speed of token generation. Asking a team to find a model that is simultaneously the cheapest, fastest, and highest-quality is asking for something that does not exist today.

This creates a genuine product decision: which tasks justify the latency cost of a premium model, and which tasks are better served by a fast, cheap model that responds in under two seconds?

The answer is rarely “use the premium model for everything.” The answer is intelligent routing, tested and calibrated against real usage data — starting with the best model available, stepping down until quality degrades unacceptably, and locking that configuration in code.

The teams that get this right do not debate model selection philosophically. They instrument their systems, measure outcomes, and let data drive the routing policy.

Common anti-patterns that undermine AI product sustainability

The same failure modes appear repeatedly across AI product teams, and most of them are architectural decisions made too early or not made at all.

Avoiding these patterns at the architecture phase is dramatically cheaper than refactoring around them after a product is in the hands of paying customers.

Key Takeaways

• Model fallback is a product decision, not just a reliability pattern, but it directly determines whether pricing is sustainable when infrastructure fails or changes
• Intelligent routing at 20x cost variance is the difference between a product with healthy margins and one that bleeds token costs at scale
• Financial observability at the operation level is what makes pricing strategy possible — without it, teams price on assumptions and discover the reality in their cloud bills
• Value-based pricing outperforms token-based pricing for adoption, retention, and margin sustainability across every user segment
• Guardrails protect brand trust and compliance, not just infrastructure costs, and their UX matters as much as their technical implementation
• Robust architecture is not just about reducing cost: it is a lever for revenue, retention, and long-term product viability

Building a Private AI Notetaking Platform That Powers Secure Workflows: Knapsack case

Cheesecake Labs partnered with Knapsack to re-architect their AI platform — evolving it from a fully local prototype to a hybrid, compliance-first system ready for enterprise scale.

“We couldn’t have solved some of the complex problems to deliver this product without the support of Cheesecake Labs’ team.”

Mark Heynen — Co-Founder & Chief Product Officer, Knapsack

Build AI products that last

The gap between an AI prototype and a production-grade AI product comes down to decisions made about model fallback, routing, observability, and pricing—long before most teams even consider them.

At Cheesecake Labs, we help product teams make these decisions right from the start by building AI systems that are resilient, cost-aware, and designed to scale sustainably.

The post 17000 characters appeared first on Cheesecake Labs.

In this post, we’ll show you how to create a Stellar smart contract and discuss how best to use Stellar’s Soroban and its flexible features.

Table of Contents

1. asd
2. asd
3. asd
4. asd
5. asd

Bond tokens

• asd
• asd
• asd
• asd
• asd

In finance, bonds are securities in which the issuer owes the holder a debt. After a period of time, the bond issuer pays all holders the bond’s value and the interest rate.

This is beneficial for the users, who profit from the purchase of bonds, and for the issuer, who can conduct business using the money used to buy the bonds before they’re paid out.

For our use case, we will treat the bonds as tokens, which users can buy and trade.

ERC-20 Tokens

The ERC-20 is a popular standard of Fungible Tokens used to ensure that each token is created using the same methods as another token.

It is an essential tool for interoperating with other contracts because it allows integration with the token without needing to know the details of its implementation.

For our use case, it will represent our bond token and the payment token, which will be used to buy bonds and pay debts.

The Soroban interface based on the ERC-20 token standard can be found in the official Soroban documentation. We are using this compiled interface, which can be found in the Soroban examples repository.

Writing the smart contract

Before we begin, let’s take a look at the logic of our smart contract.

There are two types of users: the Admin, who manages the contract, and the Users, who can buy the bonds and cash out when allowed.

The administrator is responsible for managing the contract and determining when a bond can be bought, how long it will appreciate in value, and when users can withdraw their money.

Some extra management actions are also allowed, like managing which users can buy the bonds or pausing purchases temporarily. Finally, the admin can also withdraw the money received to pay the bonds.

The users can perform two actions — purchasing a bond and cashing out. They can only perform these actions can in the periods set by the admin and if they have the necessary authorization.

The appreciation of the bond occurs over a period determined by the administrator, bound by the start date and the end date. The purchase period of the bond is not directly linked to this period and can occur at different intervals.

Contract attributes like which tokens will be used, interest rate, interest type, and interest time interval are customizable and are set at initialization. We will discuss this in more detail in the following sections.

Initialization

The initialize function sets the contract attributes right after its deployment. We won’t go too deep into its implementation, but it is essential to understand the parameters it receives.

impl BondTrait for Bond {
	...
	fn initialize(
      e: Env,
      admin: Identifier,
      payment_token_id: BytesN<32>,
      bond_token_name: Bytes,
      bond_token_symbol: Bytes,
      bond_token_decimals: u32,
      price: i128,
      fee_rate: i128,
      fee_days_interval: u64,
      fee_type: InterestType,
      initial_amount: i128,
  ) {
		...
	}
}Code language: Rust (rust)

Some considerations about these parameters:

Next, we will dive a little deeper into some of the core components of the contract, starting with the buy.

Buy bonds

impl BondTrait for Bond {
	...
	fn buy(e: Env, amount: i128) {
	    if read_state(&e) != State::Available {
	        panic_with_error!(&e, Error::NotAvailable)
	    }
	    if !check_user(&e, &(e.invoker().into())) {
	        panic_with_error!(&e, Error::UserNotAllowed)
	    }
	    increase_supply(&e, amount);
	    // Total will be the Bond amount multiplied by Bond price
	    let total = current_price(&e) * amount;
	    ...
	}
}Code language: Rust (rust)

For a user to be able to buy a bond, the purchase must be available, and the administrator must authorize the user. If the user satisfies these requirements, the supply (the amount of bond sold) increases by the amount the user intends to buy.

After this, it is necessary to calculate the bond’s current price. This is because the bond starts at a certain price but gets more expensive as time passes. Let’s look at the current_price function that performs this calculation.

fn current_price(e: &Env) -> i128 {
    let mut end_time = read_end_time(&e);
    let now = e.ledger().timestamp();
    // If the end date has not passed yet
    if now < end_time {
        end_time = now;
    }
    let initial_price = read_price(&e);
    // Calculates the amount of time intervals that have passed
    let time = (end_time - read_init_time(&e)) / read_fee_interval(&e);
    // If no time interval has passed, the price does not change
    if time == 0 {
        return initial_price;
    }
    let fee_type = read_fee_type(e);
    match fee_type {
        InterestType::Simple => {
            return initial_price + (initial_price * (time as i128) * read_fee_rate(&e)) / 1000;
        }
        InterestType::Compound => {
            let fees = 1000 + read_fee_rate(&e);
            return initial_price * (fees.pow(time as u32)) / 1000_i128.pow(time as u32);
        }
    }
}Code language: Rust (rust)

Here we need to calculate how much time has elapsed between the bond’s start date and now unless the end date has already passed, in which case, we will calculate the time between the start date and the end date.

With the time calculated, we need to determine how many time intervals have passed. For example, if our interval is one week, and 40 days have passed since the starting date, this value will be equal to 40 mod 7 = 5. In Soroban, all divisions are integer divisions, so we don’t have to worry about the modulo.

Our contract gives the flexibility to apply simple or compound interest, depending on the choice made at initialization. The calculation for each type of interest follows the standard logic of the mathematical interest formula, except for the 1000 factor. The factor 1000 added in each of the operations neutralizes our interest rate, which is multiplied by this value.

impl BondTrait for Bond {
	...
	fn buy(e: Env, amount: i128) {
	    ...
	    // Total will be the Bond amount multiplied by Bond price
	    let total = current_price(&e) * amount;
	    let invoker: Identifier = e.invoker().into();
	    transfer_from_account_to_contract(&e, &read_payment_token(&e), &invoker.clone(), &total);
	    transfer_from_contract_to_account(&e, &read_bond_token_id(&e), &invoker.clone(), &amount);
	}
}Code language: Rust (rust)

impl BondTrait for Bond {
	...
	fn withdraw(e: Env, amount: i128) {
	    check_admin(&e, &Signature::Invoker);
	    if read_state(&e) == State::CashOutEn {
	        panic_with_error!(&e, Error::AlreadyCashOutEn)
	    }
	    transfer_from_contract_to_account(
	        &e,
	        &read_payment_token(&e),
	        &e.invoker().clone().into(),
	        &amount,
	    );
	}
}Code language: Rust (rust)

impl BondTrait for Bond {
	...
	fn en_csh_out(e: Env) {
	    check_admin(&e, &Signature::Invoker);
	
	    let state = read_state(&e);
	    if state != State::Available && state != State::Paused {
	        panic_with_error!(&e, Error::NotAvailable)
	    }
	
	    // Check if end time has passed
	    if e.ledger().timestamp() < read_end_time(&e) {
	        panic_with_error!(&e, Error::EndTimeNotPassed)
	    }
	
	    // Check if the contract has the amount of payment tokens to
	    // pay the users
	    let amount_payment = current_price(&e) * read_supply(&e);
	    let contract_balance = token_balance(
	        &e,
	        &read_payment_token(&e),
	        &Identifier::Contract(e.current_contract()),
	    );
	
	    if contract_balance < amount_payment {
	        panic_with_error!(&e, Error::NotEnoughTokens)
	    }
	
	    write_state(&e, State::CashOutEn);
	}
}Code language: Rust (rust)

After the conditions are met, the contract state is changed to allow cash out.

Cash out

The cash out is performed by reading the user’s balance and checking how many bonds they have on their account. The amount of payment tokens transferred from the contract to the user’s account is the number of bonds they own multiplied by the bond’s current value.

impl BondTrait for Bond {
	...
	fn cash_out(e: Env) {
	    if read_state(&e) != State::CashOutEn {
	        panic_with_error!(&e, Error::NotCashOutEn)
	    }
	
	    let invoker: Identifier = e.invoker().into();
	
	    // Get the user Bond Token balance
	    let bond_balance = token_balance(&e, &read_bond_token_id(&e), &invoker.clone());
	    // Calculates amount of payment token
	    let total_payment = bond_balance * current_price(&e);
	    // Decrease supply
	    decrease_supply(&e, bond_balance);
	    // Transfer amount of payment tokens from contract to user
	    transfer_from_contract_to_account(
	        &e,
	        &&read_payment_token(&e),
	        &invoker.clone(),
	        &total_payment,
	    );
	    // Burn all the Bond tokens from user
	    burn_token(
	        &e,
	        &read_bond_token_id(&e),
	        &Signature::Invoker,
	        &invoker,
	        &bond_balance,
	    );
	}
}Code language: Rust (rust)

This implies that no matter how much the user paid for the bond, they will always get their money back at a higher price. For example, if user A bought 100 bonds and user B bought 100 bonds a few months later, both users will receive the same number of payment tokens at the cash-out.

The key difference is that the profit of user A will be higher as they paid less for the bond initially than user B.

After transferring the payment, the user’s bonds are burned. This transaction is only possible because the current contract is the admin of the bond token contract.

Learn more about the blockchain with Cheesecake Labs

This post has outlined the core components of a bond sales contract. If you would like to explore the rest of the functions in more depth, you can take a look at the source code.

You can learn more about the Stellar network, cryptocurrency wallet development, and the basics of blockchain on the Cheesecake Labs blog. And sign up for the Cheesecake Labs newsletter to get the latest updates delivered to your inbox.

As a Stellar Integration Partner, Cheesecake Labs is an excellent choice to help you bring your ideas for blockchain projects to life.

Get in touch and tell us about your project!

The post How to use Stellar’s Soroban to write a bond smart contract appeared first on Cheesecake Labs.

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Check out our case studies

Check out our case studies

Check out our case studies

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The post Post with all graphic elements. appeared first on Cheesecake Labs.

Read on to learn more about this ranking and what it means for Cheesecake Labs. 

A top choice for nearshore development

For us, one of the most exciting affirmations of the Clutch positioning is that it further evidences Cheesecake Labs’ authority for nearshore development. We’ve always been proud of our nearshore development offer — partnering with companies across the world, but still within the same or similar time zones. But now we’ve got the title of top web app development company in Latin America to support our own beliefs!

Cheesecake Labs can provide quality and timely service to our partners (and future partners!) across those time zones close to Latin America — North America, Europe, etc. — as well as in the country itself. Businesses can partner with Cheesecake Labs knowing that they’re going to get the best of the best when it comes to software design and development services. 

Web app development company in Latin America: how Clutch ranks companies

To understand why this is such an honor, it’s important to look at how Clutch ranks companies. Below are the criteria that Cheesecake Labs and its competitors were judged on before being granted this ranking. 

Ability to deliver

The first metric used to determine Clutch’s ranking is a business’s ability to deliver. This metric is divided into three different segments, which you can see broken down below. 

References and reviews

Understandably, the most heavily-weighted metric that Clutch considers when ranking a company is the references and reviews that a business receives. This is firsthand experience that customers have with that company, making it incredibly valuable data. 

Clutch considers factors such as how likely a customer is to recommend a business to their colleagues, how happy they are with their service, and the quality of the deliverables received. 

Clients and experience

Next, Clutch looks to the clients and experiences of clients with a particular business. They consider how satisfied clients are as well as how the business delivers on complex project demands. 

This is done by interviewing past and present clients and reading through case studies from the company. You can check out Cheesecake Labs’ use cases here.

Market presence

Clutch then looks at the market presence of the business. They want to know how clear the marketing information is, how positive the opinion of the company is, whether or not they’ve received any accolades, if they have a social media presence, and so on. 

Our blog — jam-packed full of information to help clients understand our development approach and learn the fundamentals — is available to read anytime. 

Areas of focus

The second metric used to determine a Clutch ranking is areas of focus. There are one to three areas of focus per company, with each being evaluated with quantitative data. 

A Clutch analyst will comb through this data and plot it on a matrix, at which point it is compared to the data of other businesses competing for the ranking. It’s a time-consuming and meticulous process — and one that requires careful consideration. 

This makes this metric particularly competitive and therefore an even more impressive win for the entire team here at Cheesecake Labs. 

Feedback from our amazing customers

“Cheesecake Labs’ talent is impressive. Their resources are all based in Brazil, and working with Brazilian developers has been a new experience for me. Their work ethic has been unmatched. On top of that, they’re highly educated and serve as experts in the field.”

“I’m based in Switzerland, so collaborating with someone across the Atlantic Ocean isn’t easy when it comes to development. However, the team at Cheesecake Labs is impressively well-connected on different communication systems like Slack, Jira, and video conferences. There were no issues. I was miles away, but it felt like their friendly team was sitting in the same room.”

Thank you for being a part of what makes Cheesecake Labs great!

As proud as we are to be recognized as the best web app development company in Latin America, we couldn’t have done it without all of the wonderful customers, partners, and clients that make Cheesecake Labs what it is. Thank you for your support — you can look forward to more great service from the team as we grow bigger and better as a digital partner.

The post Cheesecake Labs: #1 web app development company in Latin America appeared first on Cheesecake Labs.

Clutch is the authority for assessing software design and engineering companies. They evaluated over 24,000 organizations on a combination of client reviews, past work, market presence, and specialization before naming Cheesecake Labs on its top seven leaders list.

This recognition belongs to our team of over one hundred strategists, designers, engineers, and project managers. They’re the driving force behind our ability to build delightful digital products.

Top 7 mobile app development company: a history of excellence

Since 2013 we’ve built incredible mobile apps — with some even more incredible clients. We’ve collaborated with our partners to build more than two hundred successful tech products solving real-world problems and driving growth for startups and well known enterprises.

When our clients’ ideas combine with Cheesecake Labs expertise, something magical happens. We’ve brought innovative technologies to life ranging from intelligent rewards platforms for mobile gamers, to Europe’s first helicopter booking site and blockchain banking solution.

The last few years have brought new challenges to every business. More apps have been developed in a shorter timeframe than ever before to accommodate the world’s new ways of working. Our process, speed and efficiency have helped our clients release their app in time to make a difference for their customers.

Proud partners for great apps

Happy clients help boost a Clutch score. Here’s what just a small selection of our past customers have said about working with Cheesecake Labs, the top 7 mobile app development company.

“Cheesecake Labs has been a valuable partner to us. They’ve guided us through the journey, and the team has been proactive — this is truly important for a company like ours. As first-timers in the IoT world, we’re glad that they approach the project from our perspective. They consider what we don’t know and our challenges, and then they anticipate issues and find solutions for us.” – Nan Jiang, VP, Bemis Manufacturing Company

“Everyone we worked with at Cheesecake was very enjoyable to interact with, and always asked for our input on key design and functionality decisions without being overbearing. Their UI work was very impressive, and they made several great improvements to the functionality that we hadn’t even thought to ask for” – CEO, Retail Investor Platform

Amazing apps on exciting technologies

To be the top 7 mobile app development company, Cheesecake Labs uses the right technologies, SDKs, frameworks, and platforms to make your application successful on every device it needs to reach.

If you’re sprinting to deliver an app for iPhone users and need an iOS native app, our developers speak fluent iOS. If your target is a device-agnostic app for Android phones, then our team of Android experts can’t wait to dig their teeth into it. Over the past 9 years, we’ve done it all, and we’re looking forward to the next challenge.

Just look at the pioneering mobile apps we’ve built like Faced which provides Facial Recognition Payment (FRP) systems. We developed and validated the innovative technology using appropriate SDKs ensuring it could run on iOS as smoothly as it ran on Android.

Our comfort with frameworks like React Native and Flutter means we can move swiftly from design through development without having to build everything from scratch. We already use the best-in-class tools. It’s another benefit of dealing with a dedicated mobile app development team.

“I found Cheesecake Labs through Google and hired them after interviewing multiple companies. They were one of the touted companies that had Flutter development as one of their core competencies… Cheesecake Labs’ talent is impressive. … Their work ethic has been unmatched. On top of that, they’re highly educated and serve as experts in the field.” – Collin Goodwin, CTO, Volo Real Estate

Are you ready to join us?

It’s wonderful here in the top ten, and there’s nothing stopping you from joining us. Whether your idea could streamline your organization’s existing workflows, take advantage of AI, or be the next big thing in Web 3.0, Cheesecake Labs is your technical partner to make your mobile app a reality sooner than you think.

Write us a message or give us a call at (415) 766 8860. One of our consultants will contact you within 24 hours or less.

The post Cheesecake Labs: Top 7 mobile app development company worldwide appeared first on Cheesecake Labs.

So how do we cook up the best Cheesecake leaders? Here’s our secret recipe for success. 

Why focus on leadership development?

So glad you asked! All of our “Cakers” live by the Cheesecake Labs values: 

• Take ownership and be responsible
• Respect people and embrace differences
• Collaborate and help others grow
• Deliver a WOOOW service

And we believe that the best way to live up to these values is through personal and professional development. That’s why we have several leadership development initiatives to give each Caker the support they need and help each leader become the best leaders they can be. 

What does leadership look like at Cheesecake Labs?

Leadership starts with hiring. We look for naturally curious, self-aware people when we’re hiring new Cakers (something we’ve done a lot of in the last few years as we’ve grown to 100 Cakers!). We believe that self-awareness is key to becoming a good leader. After all, you need to be able to manage and lead yourself before you can confidently lead others. 

And we find this self-awareness also helps create a cohesive team. Before the pandemic, we were a tight-knit team working together in an office. But we’ve had to adapt to remote working just like the rest of the world. And now, Cheesecake Labs is a remote-first company, letting everyone live their best work-from-anywhere life. Transitioning our team to fully remote working wasn’t easy, but we’re proud to say that we’ve managed to not only survive but thrive out of the office. And that’s large because of our agile culture that highlights transparency and accountability. 

Leaders at Cheesecake Labs focus on building bonds between team members and creating a welcoming, safe work environment. As Guilherme Rodrigues learned in our leadership acceleration program, “Mistakes aren’t mistakes, they’re lessons. And with the emphasis on ‘learning by doing’ I get to take all the advice I’m hearing and put it into practice immediately.”

That’s a motto we live by — mistakes aren’t failures. They’re valuable learning opportunities. And creating an environment where people feel safe to make mistakes is essential to everyone’s success. 

Every voice is heard

But just because some team members have titles like “Tech Lead” doesn’t mean that they’re the only leaders in the company. Every Caker is a leader in their own way. And our culture of feedback and communication is essential for fostering and maintaining a company where everyone has a say. Sure, senior leaders give feedback to more junior Cakers, but the batter flows both ways! Anyone can give feedback to anyone at Cheesecake Labs. 

And each month, we do an Employee Net Promoter Score where we check in with each Caker to see how they’re feeling in their job, any concerns they have, and any feedback they’d like to offer up. We’re not just looking to create “bosses”. Instead, at Cheesecake Labs, we want to develop humanity leaders. Our leaders listen to the people they work with, not just for the sake of the business but for everyone’s happiness and wellbeing. 

Autonomy is key

While you can go to the store and buy a cheesecake, no sweat, sometimes it’s better to put in the extra effort and make one from scratch. The same can be said for leadership development. Every leader in our program doesn’t just learn how to assign tasks and projects — they do them as well. 

We truly believe that this is the best way to create confident and compassionate leaders. Leadership isn’t just about managing people from a distance. It’s about empathizing with your team — knowing how it felt when you were in their shoes, knowing what help and support you would need, and offering up that support to them. 

Strategy, culture, and connection

As we’ve learned through remote working, leaders are essential. Because we don’t all see each other in the office anymore, our leaders must act as the main point of contact between their teams and the company and between team members. Each Cheesecake leader serves as a central hub, connecting everyone they work with to the company strategy, culture, and values. 

And this connection makes it possible for Cakers to keep up with the break-neck speed of the projects we take on. Everything we do moves fast, and it’s up to our team leaders to make sure nobody gets left behind. Leaders listen to and support their teams whenever needed and have regular meetings and check-ins to ensure everyone is on the same page. 

Keeping the wheel of cheese rolling along

Everything we do at Cheesecake Labs is a push and pull process. And training leaders is no exception. As much as we can teach people about leadership development, management skills, and conflict resolution techniques (all of which are part of our leadership training programs), it’s also imperative that leaders in training get feedback from the people they’re leading. And that’s where our flat structure really shines. Since every Caker is used to giving feedback to everyone, teams must feel comfortable giving feedback about the performance and management of their leaders. 

And as a lean organization, one of our most important goals is to always remain resilient. Change will come. We’ve all seen it happen before our eyes. So being able to adapt to change, to bend and shift things as needed, is critical for success. 

That’s where this push and pull process truly shines. If something isn’t working, we can take the time to discuss it and either come up with a solution or rework our processes to better address the problem. 

Cheesecake Labs has gone through a massive transformation from a small startup to a bustling company, and our commitment to staying agile and nimble has helped us along each step of the journey. That’s why a leadership development program is essential.

How to be a big cheese

So let’s boil all this down — how do you go from a babybel mini cheese (or a Cupcaker, as we call our trainees) to a big cheese at Cheesecake Labs? Here’s how we do it:

• First, you learn by doing. Every Caker hits the ground running on their first day with a checklist of tasks to complete, questions to answer, and people to meet with. If you’re interested in becoming a leader in the company, we’ll encourage you to pursue that dream from day one!
• Next, you learn to walk your talk. Our values aren’t a piece of paper on the wall. They’re a key consideration of everything we do. So we’re always looking for ways to stay accountable, stay open-minded, stay collaborative, and deliver the best possible work we can. And by “we” we mean all Cakers, no matter the career level.
• Then, if you’re interested in becoming a Cheesecake leader, you can join one of our leadership development programs. These training programs will help guide you through all the ins and outs of team management by teaching you important skills. You’ll learn how to manage a team, manage accountability, resolve conflict, how to be empathetic and emotionally available to everyone you work with, and so much more!
• Finally, you keep going. Keep learning, keep moving, and keep working. We don’t slow down at Cheesecake Labs. We’re always looking for ways to improve ourselves and our company, and we firmly believe that the more you put in, the more you get out. Each Caker dedicates themselves to improving personally and professionally. We’re always ready for change and always ready to learn. 

Become a Caker and join the Cheesecake Labs team!

If you’re interested in learning more about what it’s like to be a Caker, be sure to read our blog post What’s it like to work at a top 10 mobile app company. And if you think you have what it takes to be a big cheese, take a look at our current openings! We can’t wait to hear from you!

The post The Cheesecake Labs approach to leadership development appeared first on Cheesecake Labs.

We’ll cover what CBDC is, how it compares to other currencies, and how this quickly maturing tech can be applied in the real world. 

What is CBDC?

CBDC is short for Central Bank Digital Currency. It refers to cryptocurrencies that are developed, issued, and managed by a central bank. If that sounds a bit like traditional, physical money, it’s because it is. 

The idea behind CBDC is to have a stable, digital alternative to fiat currencies. While many crypto coins want to replace or work adjacent to traditional currency, CBDC coins are designed to exist in the same space as fiat currency. 

CBDC coins are typically issued by a governing body’s bank and are tied to the value of that bank’s fiat currency 1-to-1. 

In other words, a country with CBDC coins will have physical coins, paper money, and digital money, all of which follow the same value system and can be spent, earned, and transferred in all of the same ways. 

CBDC vs. stablecoins vs. fiat currency

Those who are more familiar with cryptocurrency may think that this sounds a bit redundant. After all, isn’t this what stablecoins already do? And if you can already send fiat currency to someone digitally using an app and a credit card number, why do you need CBDC?

First, let’s define each of these terms:

• CBDC is a digital representation of a fiat currency
• A fiat currency is traditional, state-issued money (the U.S. dollar, for example)
• A stablecoin is a cryptocurrency whose value doesn’t fluctuate (so it isn’t an investment like many cryptocurrencies, but a true currency that you can spend without the value fluctuating)

Hopefully, that gives you a better idea of what sets these currencies apart. In practice, someone would use a physical fiat currency in most cases, a CBDC when spending fiat currency digitally (as it’s faster and more cost-effective, especially across borders), and a stablecoin as a separate activity whenever they see fit. 

The rise of CBDCs

While the idea of a CBDC may be new to many, CBDCs are already beginning to take off. Around the world, national banks and regulators are developing CBDC technology to provide individuals with a cryptocurrency option that isn’t risky, volatile, or unfamiliar. 

Here are some of the most promising CBDC endeavors around the world. 

Bank of Canada: Project Jasper

Project Jasper was started by the Bank of Canada in 2017 through an experimental partnership between the public and private sectors. The bank is working with distributed ledger technology (DLT) and is leveraging a partnership with private cryptocurrency bodies to better understand how to use DLT. 

Today, Project Jasper is in the midst of Phase 4. During this phase, the Bank of Canada is working on using the technology to enable cross-border transfers using DLT. This will allow larger sums of money to be transferred more quickly and at a lower cost. 

Monetary Authority of Singapore: Project Ubin

Project Ubin is run by the Monetary Authority of Singapore and is another collaborative effort between the public and private sectors. They’ve also been exploring the practical applications for blockchain and DLT technology, specifically for settling payments and securities. 

This has been a multi-phase and multi-year effort, with each phase of the project looking at a new and pressing concern. The fifth and final phase of Project Ubin, which ended in 2020, proved the business value of blockchain payment networks by showing that they were more cost-effective and efficient in the workplace, a conclusion it came to by working with the Bank of Canada. 

The Bahamas: Sand Dollar

The Central Bank of The Bahamas has taken a much more practical approach to the world of CBDC. Rather than experimenting with the technology, it’s been actively working to bring it to its marketplace. 

The ultimate goal is for project Sand Dollar to be interoperable with existing payment services channels so that all payments services firms can access the currency. 

Nigeria’s eNaira

Another interesting endeavor in the world of CBDC comes in the form of Nigeria’s eNaira. eNaira is a CBDC designed to act as a medium of exchange and a store of value, offering better payment prospects for consumers when compared to cash payments.

Nigeria is the first country in Africa to launch a CBDC, making this a particularly innovative effort. It’s also one of the most robust and finished of its kind, with several layers of security, tight control over the supply, and processes in place for distribution. 

Benefits

There are several benefits to this uniquely developed CBDC.

Improve availability and usability of central bank money

eNaira improves the availability and usability of central bank money. By offering a digital alternative to the fiat currency of Nigeria, the Central Bank of Nigeria is helping its citizens make purchases with whatever tools they have at their disposal. 

It’s an excellent example of embracing a technology (rather than rejecting or limiting its potential) to provide new opportunities for individuals. 

Support resilient payment ecosystem

The development of eNaira is also helping to build a more resilient payment ecosystem. By introducing this technology and diversifying how Nigerian money can be spent and invested, the country is making strides in strengthening its financial infrastructure. 

This is helping future-proof the country’s financial structure, setting up a brighter future for it and its inhabitants. 

Increase revenue and tax collection

eNaira can be used for tax collection, providing a faster and more accessible solution than traditional methods. And it can increase the revenue collected from taxes by reducing the costs associated with collecting these taxes. 

Enables direct welfare disbursements to citizens

eNaira has the benefit of being a direct connection for services like welfare disbursements. This allows the service to provide critical resources to individuals instantly. 

Not only that but these resources are delivered via a medium that is more accessible to the average person and more readily spendable, especially as infrastructure continues to be updated. 

Ukraine’s CBDC pilot and Cheesecake Labs’ involvement

Our last real-world example of CBDC is one that the Cheesecake Labs team is working on! Ukraine’s CBDC pilot endeavor through Tascombank is working on launching an electronic version of the Hryvnia, which will allow for the handling of payroll for public sector employees. 

It’s packed with the same tight level of control and security as the other examples mentioned in this post, along with some unique features. 

Uses the Stellar network

Ukraine’s CBDC is built on the Stellar network. Stellar is a blockchain network that allows entities to create cryptocurrency versions of real-world assets. 

For that reason alone, it’s a no-brainer to use this platform for CBDC development. It’s tailor-made for this use case and already has much of the infrastructure in place, allowing the project’s development to accelerate.

Cheesecake Labs is working directly on the pilot as a Stellar Development Foundation partner

Additionally, Cheesecake Labs is a Stellar Development Foundation (SDF) partner, giving our team insights and resources perfect for developing this project. Specifically, we’re supporting the SDF development team in redesigning the integration layer called NUMA. 

Cheesecake Labs is working with projects around the world to push CBDC and blockchain development

Ukraine’s CBDC pilot is just one of the many ways Cheesecake Labs pushes innovation in the blockchain sector. You can read more about our innovative approach here or reach out to our team today to discuss blockchain opportunities for your organization.

The post How blockchain can reshape the global economy with CBDC appeared first on Cheesecake Labs.

10 mobile app company: implementing our values from day one

A company without clear values is like a cheesecake without the cheese — it’s just not right! So we made sure to clearly define our key values and designed our company culture around them. 

The Cheesecake Labs values are: 

Take ownership and be responsible 

We align expectations, set boundaries, and work hard to find the best solutions. We assume responsibility, take the initiative, and communicate clearly to keep all parts in sync.

When you join Cheesecake Labs, you become a “Caker,” and our values guide a Caker’s experience from day one. New Cakers are given a chance to hit the ground running with a checklist on their first day. That list includes the standard employee onboarding information, but it’s more than that. We set you loose and have you learn by doing. You have to discover some things on your own, find the right people to answer your questions, and then meet with team leaders to learn more about what each team does within the company.

This approach gives new Cakers a sense of empowerment and ownership over their entry into the company. And it lines up with our first value: take ownership and be responsible. Each new Caker is trusted to take responsibility and make their new role their own. The rest of the team is there to support you (of course), but we believe that the best way to get your feet wet is to just jump in!

Respect people and embrace differences 

We stand for well-being and respect. Our diversity helps us build more creative and innovative solutions. Our partners have different backgrounds and offer exciting problems to solve.

We truly believe that the best team is made up of all different kinds of people. The more diverse our team, the more unique our approach to our work can be. We are an equal opportunity employer and look for the best person for the job, no matter what. 

And we often find that when we’re celebrating and embracing each other’s differences, that’s when we grow and learn the most. For example, every year, we celebrate Pride. But we don’t just add rainbow flags to our email signatures and call it a day. 

Instead, we set aside time to get together and host our own Pride Week. This event brings different people together to discuss experiences and issues in the LGBTQIA+ community. Our goal is to learn more each year and promote important discussions that support the LGBTQIA+ community — both in and outside of Cheesecake Labs. 

It’s our goal to create a workplace where everyone feels 100% safe to be exactly who they are. Because we can only do our best work when we’re able to be our best selves.

Collaborate and help others grow

We grow and learn faster together. We share knowledge with the community and go beyond to help others succeed.

One of the things we most look for when hiring new Cakers is a willingness to keep learning. We pride ourselves on running a business with a flat structure, where everyone can share knowledge and expertise with everyone. If it’s your first day on the job and you know something that would help someone who’s been at Cheesecake Labs for five years, we want to hear it! We operate on a system of continuous learning and are always looking for ways to expand our knowledge base. We’ve found that collaboration is, hands down, the absolute best way to learn. 

We’re also dedicated to mentorship and professional development. You’re supported and guided through a one-to-one mentorship from your first day. Your mentor acts as your leader through the ups and downs of life at Cheesecake Labs. And with them, you always have a safe space to express your ideas — but also your fears, insecurities, concerns, and more. 

And don’t think that you won’t have a voice at Cheesecake Labs just because you’re new on the job. We operate a flat structure that thrives on feedback. And we’re not just talking about feedback from senior team members to fresh oven Cakers. Anyone can offer up or request feedback from anyone else at any level of the company. You’ll even see Cupcakers (our trainees!) giving feedback to senior staffers. We believe that we’re all on this journey together — so it’s vital to learn from each other and find ways to contribute to and improve our company culture. 

Deliver a WOOOW service

We encourage original thoughts and ideas to propose creative and innovative solutions, aiming to exceed expectations with win-win partnerships.

Sometimes, clients come to us with unique problems that need unique solutions. And we’re a very fast-paced company. Ask any Caker, and they’ll tell you that three months at Cheesecake Labs is like a year anywhere else. So we encourage people to be creative and agile in their work. 

We want to find the absolute best solution for our clients and blow them away with our deliverables. Whether that’s investigating new technologies or features, reaching out to partners for advice, or putting together beautiful, fully-featured and functional applications for clients in record time, we’re all about big ideas and big results. 

We already have 100 Cakers — you could be next!

If becoming a Caker sounds like something you’re interested in, check out our current openings and apply! You’ll get all the benefits and support you need to be the best Caker possible. We think that we do a really good job of creating an exciting, engaging, and supportive environment that lets you do your best work. 

Sure, you get a job when you come to work for us. But you’re also getting so, so much more. We offer a unique benefits package that includes a monthly dolar bonus, a credit card for flexible benefits so you can use it according to your needs, a fully-loaded Macbook Pro, Gympass discounts, health and dental insurance, Free remote English classes, a budget for personal and professional development, and the choice to work wherever you want. 

But, more importantly, you’re joining a welcoming, supportive community of high-performance professionals. 

But don’t just take our word for it. Here’s what some of our employees have to say: 

“I have just joined the company and have already been taken by a huge feeling of belonging…The environment is dynamic and encourages autonomy, but at the same time, the teams are united…Even after only 16 days, I feel at home among friends.” 

• Diefani Piovezan, Software Engineer

“Have you ever walked into a party and felt like the most popular person in the room — where everyone’s like, “Hey man, great to see you!” or “I’m so glad you could make it”?

Now imagine having that feeling every morning when you switch on your computer to log in to work. That’s what my first few months in the Cheesecake Labs team have been like. And, for my first full-time job in mobile development, I couldn’t be more psyched to be part of this culture.”

• Érico Rosiki Weber, Mobile Engineer

“Sure, we’re a software design and engineering partner, but technology isn’t the only thing that matters here.

Professional and personal development is something that’s always been a priority for me — and that’s echoed back by the Cheesecake Labs team 100%. After all, the better we feel in the jobs we’re doing, the better job we can do for our clients.” 

• Guilherme Rodrigues, Tech Lead

Come join the Cheesecake Labs team and experience what it means to work at a top 10 mobile app company for yourself!

The post Why work in a top 10 mobile app company? appeared first on Cheesecake Labs.

What is Tokenomics?

Tokenomics is a blended word of ‘token’ referring to the crypto token and ‘economics.’

Tokenomics is all about how a crypto token is integrated into the economy. The token economy addresses all the qualities of a crypto token that make it attractive to investors. The term has become trendy in recent years and addresses the mathematics and benefits of managing crypto assets.

How does The Token Economy fit into the world of Blockchain and Crypto?

Besides looking at how the asset works, Tokenomics also considers the psychological or behavioral forces that could impact the asset’s value in the long term. These aspects can directly impact the way assets organically evolve and how you can integrate tokens into businesses and products.

Projects with a well-planned and designed token economy have a higher chance of succeeding in the long term because they incentivize people to buy and keep their tokens. On the other hand, businesses with weak tokenomics will struggle because people often sell their tokens at the first sign of trouble.

Incentivization in the Token Economy

We all are driven by incentives. Children attend school because it provides learning opportunities and a better future. The world of crypto is full of incentives. While crypto assets have captivated the world with promises of economic opportunity, those opportunities still aren’t completely tangible.

Let’s look at The Stellar Network’s token, Lumens, as an example. Lumens are used to make trading on the blockchain-based distributed ledger easier. You can efficiently trade Lumens at a fraction of a dollar cent which lowers their carbon footprint. That smaller carbon footprint incentivizes some users to choose Lumens for their transactions over other options.

Defining the core aspects of your digital asset

When preparing to launch a digital asset, there are a handful of questions you need to ask yourself (or your blockchain development partner) to help further define the asset. Let’s take a look at some of the things you need to consider. 

Decide how much control you want over the asset and the market

Different assets have different levels of authorization. These authorization levels are dictated by the asset’s intended application and the blockchain network you’re using. Tokens can be tightly controlled, or you can allow users to independently manage blockchain processes themselves. 

For example, someone launching an asset in the Stellar network may configure it to maintain tight control. This means that they might individually approve each transaction and even carry out clawback operations to enforce regulation and safety.

On the other hand, you can let users interact with the asset themselves. With this option, users also control the mechanisms built to support it. This means that they work together towards a common goal — sustaining themselves as asset holders. 

How should the supply be managed?

Depending on your use case, you can launch an asset with a fixed limited supply or a dynamic supply. Fixed supplies give you a clear idea of asset scarcity. With a dynamic supply you can control the circulation of your token depending on your strategy. You can mint new tokens to increase supply or burn tokens to remove supply from circulation.

Stablecoins tie the value of the cryptocurrency to more stable assets, like fiat currencies. With stable tokens, a ‘reserve’ is set up securely by a transparent audited account. The asset or basket of assets supporting the stable coin is stored securely in this reserve. 

Let’s look at USD Coin as an example. USD Coin or USDC is a stable coin that is a tokenized version of the US Dollar. Here’s how it works:

• Users send US dollars to the coin issuer’s bank account
• The issuer then uses a USD Coin smart contract to create (or mint) the same amount of USDC
• These minted UDS Coins are sent to the user, and the fiat currency they sent in is held in a reserve

How do assets inflate and deflate in Tokenomics?

In the open market, asset prices fluctuate according to their use. Certain projects keep a steady rate when launching new assets. They are distributed according to the rules set in the project.

Or you can manage supply through burning and minting, which you can then use to control the inflation and deflation of assets.

Here’s how burning and minting work:

• Demand increases when you burn (or use) tokens
• Supply increases when you mint (or create) tokens

So, burning and minting create a simple supply and demand relationship — if you want to control the inflation of your asset, you want more tokens to be burned or used. If you’re going to deflate your asset, you want to create or mint new tokens. Asset

How to issue your assets: initial markets and distribution

When you launch a crypto asset you need to decide beforehand if you’ll let your asset grow organically or if you want to control the initial offering and price at launch.

Here are some ways you could approach market distribution:

• Controlling the initial distribution of the market. This can be done by controlling the way users can purchase and consume the asset together with the price and value. The asset creator can control the initial distribution via an app, service, or smart contract. Trading the assets for goods is another option.
• Creating an “early adopters” program as a means of pre-distribution. This could be done via airdrops, which involves sending free tokens or coins to wallet addresses in exchange for a small service, like tweeting a post promoting the company issuing the currency, or by launching ICOs or Initial Coin Offerings.
• Setting up an initial market with a liquidity pool or more. Liquidity pools are virtual trading places where tokens are purchased and sold. A liquidity pool refers to a basket of tokens locked in a smart contract. The pool allows cryptocurrency trading by providing users with an easy way to swap tokens with each other. 

 Which networks should you use?

The blockchain network you choose will have a direct impact on your token and how it’s used. Here are a few things to consider when choosing a network.

• How user-friendly is the network? In a developed ecosystem, there are more sources and tools for users if they ever get stuck and need some help.
• What is the cost to transact? Each network has a different way they charge for transactions. For example, the Ethereum blockchain can have high transaction fees during peak times. This happens because each transaction cost is directly affected by the amount and complexity of its smart contracts. So, these smart contracts are operating in addition to these regular transactions.
• How can you program assets? Each blockchain will handle programming assets differently. Networks like Ethereum or BSC use scripted smart contracts. These allow you to create complex codes and applications in the blockchain. The Stellar network operates differently. Stellar focuses on being a payment system that keeps transaction costs low and allows users to implement light core behaviors for stable and quick performance. The network you choose should help you program assets in a way that works best for you.
• How elaborate is the implementation process? You should consider the level of complexity involved in integrating a product integration into the network. It is also important to consider the level of control a company has over its assets and markets. 

Stay on top of regulations

All aspects of the token economy must be in accordance with local regulations. In the US, this means complying with federal and state laws. Crypto is still a relatively new technology — but it’s evolving at a fast pace. As cryptocurrency becomes more popular, legal requirements are bound to change, so it’s important to keep up to date on the latest regulations. 

Partner with Cheesecake Labs for all things blockchain

Now that you know the basics of the token economy and the process of issuing your own token, you’re ready to take the next step. If you’re looking for a partner in all things blockchain development, the Cheesecake Labs team of experts is ready to help! Get in touch with us to learn more about how we can help you launch your own digital asset. 

The post How to issue a digital token to solve your business needs appeared first on Cheesecake Labs.