PoC vs Prototype vs MVP: Differences, Examples, How to Choose

According to a CB Insights report, 35% of startups fail due to a lack of market need, and another 20% fail because they get outcompeted or face technical flaws. Launching a new IT product always involves risk. Sо, to avoid writing code for a product people will not use, teams typically rely on Proof of Concept (PoC), Prototype, and Minimum Viable Product (MVP).

Choosing the wrong approach may lead to budget overruns and missed deadlines. In this article, we will break down the technical and business differences among PoC vs prototype vs MVP, provide real-world examples, and share a framework for choosing the best strategy for your product.

PoC vs Prototype vs MVP: Quick Definitions 

Before diving into the details of PoC vs. prototype vs. MVP, let's establish the baseline. All three concepts aim to mitigate risk, but they operate at different stages of the product lifecycle and test different assumptions.

One-line definition for each approach

• PoC (Proof of Concept): A technical validation of a hypothesis answering the question, "Can we technically build this digital product given our current constraints?"
• Prototype: A visualization of the product's logic, flow, and interface answering the question, "How will users interact with this product?"
• MVP (Minimum Viable Product): The first working version of a product with a minimal core feature set to validate the business model, answering the question, "Are people willing to use and pay for this?"

Common confusion points in product discovery

During the product discovery phase, the lines between these terms often blur, leading to planning mistakes:

• Confusing a PoC with a prototype. Engineers often call a piece of draft code a "prototype," even if it’s never tested with actual users. A PoC is a check that is hidden from end users. For instance, it allows for testing if a custom AI integration can securely parse healthcare records or validate transaction fees for a Web3 smart contract. On the contrary, a prototype focuses on the UI/UX experience. For example, you may need a clickable Figma mockup for a new Sport & Fitness app dashboard.
• Mistaking an MVP for a functionally incomplete product. An MVP is frequently confused with a raw, buggy beta version or an advanced prototype. Still, an MVP is not just a stripped-down product. It is a functional solution that must deliver real core value to early adopters right from the start, unlike a prototype, which is merely a simulation. For example, a fintech MVP must securely process real transactions, even if it supports only one payment method. A B2B SaaS platform must actually automate a workflow for paying clients, rather than just simulating the process.

Proof of Concept (PoC) 

A Proof of Concept is the technical reality check. Before committing substantial resources to a full-scale build, engineering and product teams use a PoC to isolate and test the most complex, high-risk technical assumptions of a new product idea.

What a PoC proves

A PoC is not focused on UX, aesthetics, or market demand. It strictly proves technical feasibility and answers binary, engineering-focused questions: Can this specific third-party API handle our expected data load? Can our proprietary algorithm process live video streams in under 50 milliseconds? Ultimately, it validates whether the core technology can actually function within the project's specific constraints.

Typical PoC outputs

The result of a PoC is rarely something you can show to an end-user, and often not even to a non-technical reviewer. Typical outputs include:

• Documented findings on technical limits and potential workarounds that assess the feasibility of the project. For example, it could be a report confirming whether a custom AI integration can securely anonymize and process healthcare patient data in real-time.
• Performance metrics that detail server load, latency, or data throughput. For instance, it can be latency test results for live data syncing from wearables to a Sport & Fitness platform.
• A rough, isolated script or backend module proving that certain logic works. Such as a raw script validating gas fees and transaction logic for a Web3 smart contract.
• Architectural diagrams or system blueprints that are based on the results the engineering team learned during the test. For example, it could be the revised data flow for a high-load marketplace recommendation engine.

When to use a PoC

You should build a PoC when technical uncertainty is the single biggest threat to your product's success. For example, you may want to launch a fintech app that relies on integrating a legacy banking system with a brand-new AI fraud-detection model. In this case, you must build a PoC to ensure the systems can communicate securely. According to Gartner's research on adopting emerging technologies, mitigating early technical risks through strict proof-of-concept testing is critical to avoid expensive architectural rewrites later.

PoC best practices

To get the most out of a PoC, teams should follow strict boundaries. At Stubbs, our team relies on several core principles to validate ideas efficiently:

• Involve technical leadership early. Applying the CTO-as-a-Service approach during the PoC phase ensures the right decisions regarding strategic technology. For example, it could be validating a Node.js backend for a high-load marketplace before committing to full-cycle development.
• Leverage low-code for speed. Whenever possible, we use low-code development tools such as Retool or Firebase to rapidly test integrations or data flows. This allows our engineers to validate the technical concept effectively without writing custom code from scratch.
• Follow strict timeboxing. We strictly limit a PoC to 1 – 3 weeks. As AWS enterprise experts note in their PoC guidelines, without an established time frame, scope creep occurs, and the PoC loses its value as a quick learning tool.
• Define binary success criteria. Before writing code, establish exact metrics, e.g., "The MongoDB database must process 5,000 concurrent queries in under 2 seconds."
• Keep it isolated. Always run the PoC in a sandbox environment so it doesn't impact your existing systems or create early technical debt.

Common PoC mistakes

1. Deploying PoC code to production is the most dangerous trap. PoC code is held together by duct tape and is inherently unscalable. It should be treated as sacrificial code to avoid massive technical debt. An example of such a mistake is deploying an untested, raw matching algorithm directly into a live marketplace, which can easily cause server crashes under load.
2. Adding a UI will produce a different testing model. Engineers sometimes waste time building a front-end for a PoC. If you are designing buttons and layouts, you have accidentally pivoted to building a prototype. Thus, IT specialists could spend their time styling a dashboard for an AI Integration when they strictly needed to prove the API could parse document data.
3. Scope creep may result in testing too many variables at once. Instead, developers should isolate the single biggest technical risk. For example, the team may validate complex smart contract logic and test multiple wallet connections simultaneously while working on a Web3 app.

Prototype 

While a PoC proves that your team can build a digital product, a prototype figures out how users will interact with it. It bridges the gap between abstract requirements and the final user experience, simulating the product’s interface and flow.

What a prototype validates

A prototype validates usability, design aesthetics, and user journeys. It answers questions like: Is the navigation user-friendly? Do users understand where to click next? Does the layout solve their problem efficiently?

Catching usability flaws here is critical. According to IBM research, fixing a usability error after development is complete can cost up to 100 times as much as fixing it during the design phase. A prototype helps to ensure you design the right thing before engineering starts.

Prototype types: low-fidelity, high-fidelity

Prototypes evolve as your product discovery progresses from low-fidelity to high-fidelity:

Low-fidelity (Lo-Fi): Rough, static representations like paper sketches or simple wireframes, e.g., Balsamiq. They are cheap, quick to create, and ideal for mapping out basic user flows and information architecture in the early stages of the project. For example, it could be sketching a multi-step checkout flow for an e-commerce store.

High-fidelity (Hi-Fi): Created in tools like Figma or ProtoPie, these are interactive, clickable mockups that look and feel like the final application. They include branding, animations, and precise UI elements, making them perfect for user testing and attracting investors. For example, a high-fidelity prototype can demonstrate a fully interactive data dashboard for a B2B SaaS platform.

When to use a prototype

You should build a prototype when your main risk is user experience or market positioning, rather than core technology. For instance, if you are designing a new digital banking interface for a fintech startup, the underlying transaction technology might already be proven via APIs. Instead, you need a Hi-Fi prototype to observe if real users can smoothly navigate the new screens to add their payment methods or split bills without getting confused and dropping off.

Prototyping best practices

At Stubbs, our UI/UX design team combines creativity with an analytical approach to ensure prototypes align perfectly with your business objectives. We follow a few core principles:

1. Focus on the flow, not just the visuals, because a beautiful button is useless if the user cannot find it. We design modern, user-focused interfaces, ensuring the core user journey works flawlessly before adding visual polish.
2. Test your prototype with real users; feedback from your internal team alone won't yield new insights. We always advocate presenting the prototype to unbiased target users to validate design decisions.
3. We treat prototypes as collaborative learning, disposable tools. Thanks to agile iterations, our team is always prepared to adapt or radically alter designs based on real user feedback before we write code.

Common prototyping mistakes

1. The "almost done" illusion. Since Hi-Fi prototypes look exactly like the final product, non-technical parties often assume development is nearly complete. This may lead to unrealistic expectations regarding deadlines.
2. Starting from high-fidelity. Skipping Lo-Fi wireframes and jumping straight into high-fidelity design often wastes time on polishing details before the core user journey is validated. For example, designers could refine 3D animations in a Sport & Fitness app before testing whether users even know how to start a workout timer.
3. Over-explaining during testing. If you have to tell a user where to click during a prototype test, the design has failed.

Minimum Viable Product (MVP) 

An MVP is the moment of truth for your business model. While a PoC validates technology and a prototype validates usability, an MVP is the first functional version of your product that you actually release to the market to validate real-world demand.

What an MVP validates

An MVP strictly validates the business case: Do users care enough about this problem to use our solution and pay for it? According to industry research, nearly 30,000 new products are launched each year, and 95% fail, primarily because there is no actual market need for the solution. An MVP prevents you from over-investing in useless products by testing your core value proposition with real users in a live environment.

MVP characteristics

Unlike throwaway PoCs or simulated prototypes, an MVP is a real, working product.  It delivers immediate, tangible value to early adopters, allowing you to measure retention and actual willingness to pay. It has a working backend, a database, and real production code, although it includes only the absolute core features required to solve the user’s primary pain point. Everything else is stripped away.

When to build an MVP

You should build an MVP when your primary risk is business viability. If the team has made a decision on technology and validated the UX, but needs definitive proof that people will adopt the product. For example, if you are launching a telehealth platform, your MVP might just connect patients with available doctors via a simple video link and a secure payment gateway. You don't need an AI symptom checker or a complex patient portal yet; you just need to prove users will pay for remote consultations.

MVP best practices

• Focus on the "Viable". The product must actually solve the problem. Using reliable technologies like Node.js and React, we build robust MVPs that deliver real value.
• Measure actionable metrics. We advise teams to track customer acquisition cost (CAC), retention, and conversion rates rather than vanity metrics like page views.
• Ship quickly. Since we prioritize speed to market, we often leverage cross-platform tools like React Native to launch on both iOS and Android simultaneously without over-engineering.

Common MVP mistakes

• Feature creep. The most common trap is adding "just one more feature" before launch, turning the MVP into a bloated, delayed release. For example, a team may build a complex multi-vendor rating system for a marketplace MVP. But in this case, a simple contact form would suffice to gauge initial demand.
• Ignoring feedback. Building an MVP is useless without a systematic way to collect, analyze, and act on user feedback. For example, a development team may launch an edtech MVP but fail to track exactly where students drop off in the learning module.
• Scaling too soon. Pouring money into marketing or heavy server infrastructure before the MVP has actually proven product-market fit. Thus, a team may optimize a corporate website for millions of visitors before confirming the core lead-generation funnel actually works.

PoC vs Prototype vs MVP: Key Differences

​Choosing the right validation method among Proof of Concept vs prototype vs MVP depends entirely on the specific risks you are trying to eliminate. To avoid burning your budget, you need to understand how these three approaches stack up against each other. Below is a comprehensive comparison table, followed by a detailed breakdown of the core differences.

Goal and success criteria

A PoC aims for a binary technical outcome (pass/fail). A prototype succeeds if users can navigate the interface smoothly without friction. An MVP succeeds only when it hits actual business KPIs, such as generating the first 100 paying subscribers for a new B2B SaaS platform.

Audience: internal vs users vs market

A PoC is strictly for your internal tech team. For example, based on a PoC, the team will validate whether a specific AI integration can securely process local data. Prototypes are shown to a controlled group of test users or early investors. An MVP is released to the open market of paying customers who will judge the product with their wallets.

Effort: time, cost, team roles

PoCs are quick, relatively cheap, and focused on the backend. Prototypes require UI/UX expertise but zero production code. Building an MVP is the most resource-intensive phase. At Stubbs, we deploy a dedicated cross-functional team (including front-end, back-end, and QA engineers) over a few months to ensure the MVP is stable, scalable, and ready for public launch.

Deliverables: code, design, data

The results of a PoC are architectural diagrams and throwaway scripts, whereas a prototype delivers high-fidelity, clickable screens. An MVP provides a fully functional application that generates real-world business data. For example, it could be live transaction volumes and user retention metrics for a fintech app.

Risk type: technical vs product vs market

Every approach mitigates a specific threat. A PoC allows for avoiding technical debt before it starts. Prototypes eliminate the risk of building a confusing user journey, which is crucial, for example, for complex e-commerce checkouts. MVPs tackle the most dangerous threat of all: spending time on developing a product that no one will actually buy.

Similarities and Overlaps 

PoC vs MVP vs prototype serve different primary purposes. Still, they are united by a shared goal in product development. They are performed to minimize risk, validate assumptions, and prevent teams from wasting resources on unproven ideas.

Where PoC, prototype, MVP can overlap

In the real world, the rigid boundaries between these three concepts can sometimes blur, especially when using modern development tools. For instance, when using Low-Code platforms, a prototype can serve as a PoC simultaneously. Thus, a clickable prototype of an e-commerce inventory dashboard built in Retool might actually connect to a live database API. This way, it will test both the technical data retrieval and the visual layout.

Similarly, in Web3, the progression is often highly compressed. A developer might write a smart contract to prove a specific token-burning mechanism within a PoC framework. At the same time, they can attach a basic frontend to see how users connect their wallets. This is the task usually performed during prototyping. If they immediately release it to a small, whitelisted group of users to test transaction willingness, they will get an MVP. All these testing forms will evolve rapidly from the same initial codebase.

How teams combine them in real projects

Our team rarely treats these approaches as isolated, mutually exclusive events. Instead, we combine them into a seamless, step-by-step product discovery and development pipeline. A great example of this pipeline is our work on Mentoly, a custom healthcare marketplace that connects clients with licensed psychologists. Here's how we structured the process:

• Step 1: Logic validation with PoC. Any marketplace requires a robust backend. Before scaling the system, we need to ensure that the underlying architecture can solve complex filtering and secure data storage. In our case, we tested how Node.js and MongoDB would handle the client's tasks.
• Step 2: User journey validation with a prototype. Before creating the final design, we focused on developing low-fidelity wireframes. This prototype enabled us to visualize the platform, gather valuable early feedback, and ensure the core functionality was intuitive for both psychologists and clients.
• Step 3: Launching and learning with an MVP. After validating the UX, we moved on to development. We launched the core platform with intelligent auto-selection, doctor profiles, scheduling, and a built-in wallet. This initial release worked like a classic MVP: the platform attracted over 1,000 active users in the first few months, proving the product's demand. We then continued to iteratively add new logic and features.

By combining these methods, we ensure that by the time the product hits the market, the main technical and UX risks are already addressed. This allowed our client to fully focus on business development.

How to Choose: Decision Framework 

To avoid wasting your budget and development hours, you need a systematic approach to product validation. The decision between an MVP vs prototype vs PoC can be made only after you have identified the single biggest threat to your product's success at this exact moment.

Choose PoC when technical risk is highest

Opt for a Proof of Concept when your primary question starts with "Can we actually build this product given our constraints?" This is critical for backend-heavy products, where a technical failure can bring the entire project down. For example, if you are building a new fintech platform that needs to synchronize high-frequency trading data between a legacy banking API and a modern digital wallet, you must run a PoC first. Before designing any UI, your engineering team needs to prove that the API can handle the heavy data load securely, instantly, and without dropping transactions.

Choose prototype when UX risk is highest

A prototype is your best tool when the underlying technology is already proven, but the user journey is complex, risky, or unvalidated. Choose this approach to answer: "How will users logically interact with our solution?" For instance, if you are developing a comprehensive B2B SaaS platform for financial analytics, the backend data processing might use standard logic. However, visualizing that dense data across complex, customizable dashboards requires a high-fidelity prototype. You need to test if enterprise users can actually navigate the interface and generate the reports they need without relying on customer support.

Choose MVP when market risk is highest

It is time to build an MVP when the technology is viable, the design flow is clear, but you need to answer the most crucial business question: "Will people actually use and pay for this?" An MVP mitigates financial and market risks. Imagine launching a new marketplace for renting heavy construction equipment. You do not need a complex AI recommendation engine or a fully automated dispute-resolution system immediately after the marketplace launch. You just need a functional, stripped-down MVP with a secure payment gateway that connects real suppliers with contractors to prove that the market is ready to book equipment digitally.

Simple checklist for startups and product teams

If you are still unsure which path to take, use this quick diagnostic table:

Typical Roadmap: From Idea to MVP 

Turning a general concept into a profitable product requires a structured approach. While every project is unique, successful teams often follow a certain roadmap to mitigate various risks. 

Phase 1: PoC (if needed)

Not every software product requires a Proof of Concept. You only need this phase if your idea relies on uncharted, complex, or high-load technology. For instance, you plan to build a fintech application that requires a new real-time, cross-border currency exchange integration. In such a case, Phase 1 involves writing isolated backend scripts. Your engineering team needs to ensure the APIs can securely sync exchange rates without timing out. If this tech solution works, you move forward. If it fails, you pivot early without having wasted your budget on design.

Phase 2: Prototype

If you are relying on standard, well-documented technology, the focus shifts to the user experience. Or if you have already conducted PoC validation and determined that the technical foundation is secure.  In this phase, UI/UX designers create low-fidelity wireframes followed by high-fidelity, clickable mockups. For a complex e-commerce platform, this means mapping out the entire customer journey, from filtering product catalogs to navigating the final checkout screen. You present this prototype to a target test group to observe their behavior. This way, you can ensure users do not abandon their carts due to confusing, non-intuitive navigation.

Phase 3: MVP build and launch

If the team validated the technology and approved the design flow, it can start building the actual product. The goal here is to speed up time-to-market and deliver core value. For example, if you are launching a B2B marketplace for wholesale suppliers, phase 3 should focus on building the main features. In this case, it should allow vendors to list their inventory and buyers to securely execute a purchase. All secondary features, like advanced AI recommendations or automated promotional emails, are pushed to the post-launch backlog.

What to measure at each stage

Success looks completely different at each development phase. To keep your product discovery on track, you must focus on the right metrics for each development phase:

• Measure pure technical KPIs at the PoC stage. Focus on server response times, API latency, database query speeds, and system stability under simulated heavy loads.
• Measure usability and friction at the Prototype stage. Track the task success rate, time on task, and qualitative feedback regarding the interface's clarity. For example, analyze whether users can successfully locate the billing settings.
• Measure business viability and market appeal of your product at the MVP stage. Shift your focus entirely to financial and growth metrics. Track customer acquisition costs, conversion rates, monthly active users, and early retention rates to demonstrate product-market fit. In relation to a SaaS product, you can measure the percentage of users moving from a free trial to a paid tier.

Examples and Mini Case Studies

Let's look at these validation methods to clarify how they can save time and money. Here are three real-world case studies illustrating how product teams apply PoCs, prototypes, and MVPs across different industries.

PoC example: integration, performance, AI feasibility

Scenario: Consider the recent rise of Cursor, the AI-first code editor that took the developer world by storm in 2023–2024. Before building complex user-facing features like multi-file AI edits, the founders had to overcome a massive technical hurdle. The challenge was in generating highly accurate AI code completions with near-zero latency.

The PoC: Their initial Proof of Concept focused entirely on AI feasibility and performance. Before designing the interface, the engineering team had to test whether they could parse large context windows and stream responses from Large Language Models (LLMs) in milliseconds.

The Result: The PoC successfully validated that sub-second AI inference and smooth data integration were achievable. When this technical risk was eliminated, the team confidently moved forward to fork VS Code and build the interface.

Prototype example: onboarding flow, dashboard UX

Scenario: A leading iGaming data provider needed a marketing tool to engage attendees at the ICE 2024 London event. They partnered with our team to build an interactive quiz platform with a complex admin dashboard.

The Prototype: For building a BETER Quiz, we had a strict two-week deadline, which placed high demands on the UX/UI design. The Stubbs UX/UI team first created detailed wireframes and visual designs to map out the entire user journey. This prototype validated the mobile flow from scanning a QR code to completing the quiz. Also, our designers visualized the SaaS-like content management dashboard for administrators.

The Result: By validating the flow via a prototype, the development team implemented a better design. As a result, we achieved a flawless launch that engaged over 100 participants during the live event.

MVP example: payments flow, core user journey

Scenario: Midjourney is the AI image-generation platform that gained popularity in 2022-2023. Its owners faced a typical choice. They could spend a lot of time developing a custom web platform. Alternatively, they could find a shorter way to gauge users' willingness to pay for high-quality AI art.

The MVP: They skipped building a custom frontend UI entirely. Their MVP launched exclusively as a Discord bot. The core user journey was reduced to a single action. Users had to type a "/imagine" prompt in a chat channel. For the payment flow, they simply integrated a basic Stripe link to handle subscriptions for heavy users who wanted faster generation times.

The Result: This MVP validated that people were willing to pay for AI-generated images. For that aim, the founders didn’t need a full-fledged web application. Their MVP strategy generated early revenue, which funded training for their AI model.

Do You Need to Code PoC, Prototype, MVP?

One of the biggest misconceptions in product development is that early validation requires writing thousands of lines of custom code from scratch. Today, the approach is much more nuanced.

No-code vs code tradeoffs

If you want to launch your digital product faster and cheaper, you can use no-code or low-code platforms. A basic e-commerce MVP or a simple marketplace directory can be built without custom programming, allowing you to test market demand fast enough. However, you will lose in scalability and customization. No-code tools suffer from vendor lock-in, rigid architectures, and poor performance under heavy user loads. Custom code will be more expensive and time-consuming upfront. Still, it will provide flexibility, robust security, and full ownership of your product's intellectual property.

When code is required

You can simulate a user interface, but you cannot fake core technical logic. Custom code is absolutely mandatory in several specific scenarios:

• Deep tech PoCs. If you are testing a proprietary data-parsing algorithm or a complex integration for a B2B SaaS platform, drag-and-drop tools will not work. In such cases, you need backend engineers to write actual scripts, for example, in a Node.js  runtime environment.
• Security & compliance. An MVP in fintech that processes real user transactions, wallets, and sensitive banking data requires a custom, highly secure architecture. You cannot rely on basic no-code templates when financial compliance is at stake.
• High-load architecture. If your product relies on syncing multiple heavy APIs simultaneously, custom backend development is required. This helps prevent server crashes and data bottlenecks.

Tools to speed up early validation

At Stubbs.pro, we leverage a mix of tools to accelerate the discovery phase before committing to a full-scale custom MERN stack development:

• For prototypes: Figma and ProPie are the gold standards for building high-fidelity, clickable user flows without writing any frontend code.
• For fast PoCs and MVPs: We frequently use Low-Code platforms like Retool and Firebase. They allow our engineering team to rapidly set up databases, user authentication, and admin panels. This drastically cuts down initial backend setup time while still allowing our developers to inject custom code where it matters most.

Cost and Timeline Expectations 

To control your expenses and set realistic expectations, you need to plan a budget for a new digital product. Treating your PoC, prototype, and MVP as distinct, timeboxed phases will help you avoid overinvesting in the early stages and underinvesting in the later stages.

What drives early-stage cost 

The costs for MVP vs PoC vs prototype depend on numerous factors, including the digital product's features and the industry it serves. A business can calculate the budget only after making decisions on tech stack complexity, API integrations, compliance requirements, and UX/UI design. For example, building a highly secure, PCI-compliant backend for a fintech MVP will naturally cost significantly more than setting up a standard inventory database for a basic e-commerce store. Similarly, requiring complex, interactive data-visualization dashboards for a B2B SaaS prototype will increase UX design hours compared to designing standard user profiles.

Rough timeline ranges for PoC, prototype, MVP

Every software project is unique, but there are baseline expectations for a typical SaaS or marketplace platform, or any other type of project:

PoC: 1 to 4 weeks | ~$3,000 – $10,000. Costs are generally low, as the focus will be only on backend engineering needed to test isolated scripts and validate API connections.

Prototype: 2 to 8 weeks | ~$5,000 – $20,000. Costs range from low to medium, determined entirely by UX/UI design and user testing, with no expensive coding.

MVP: 3 to 6+ months | ~$30,000 – $120,000+. This is a medium-to-high investment requiring a dedicated, full-cycle team to build a scalable, production-ready application.

Budgeting tips to avoid wasted spend

To protect your runway during the early stages, adhere to strict scoping rules:

• Set priorities and cut any feature that does not directly validate your core business hypothesis. If you want some features, but they are not necessary, leave them for version 2.0.
• Engage a CTO-as-a-Service early on to choose the most cost-effective architecture. For example, choosing React Native lets you launch on both iOS and Android simultaneously, saving significant development costs.
• Stick to the timebox and do not let a PoC or prototype drag on indefinitely. If a prototype costs more than $20,000 or takes longer than two months, you are likely over-engineering it and creeping into the MVP territory without realizing it.

How We Help: Discovery to MVP Delivery

Turning an abstract idea into a working product requires strict discipline and the right technical expertise. At Stubbs, we help businesses and product teams improve this journey without breaking the bank. To this aim, we offer a full cycle of services: from validating early hypotheses to launching a scalable solution.

Product discovery workshop format

Collaboration with our clients begins with the product discovery phase. We conduct introductory workshops to help us understand your business vision and target audience, and to identify potential risks. Together with a client, we create a detailed project roadmap, prioritize functionality, and determine which to test first: the technical foundation through a PoC or the user experience through a prototype.

PoC, prototype, MVP delivery approach

Our approach is built on sequential risk elimination. A great example of working with UX risks is the Assay-X project, a mobile app for tracking blood test results. The main challenge was to present complex medical statistics in a simple, user-friendly way. Instead of developing the app right away, our UX/UI team followed a rigorous prototyping process: research, rough wireframing, assembling a mood board, and finalizing the interactive design. We thought through the visualization of charts and the flow of consultations with doctors before writing code. Once the prototype was approved, we continued developing the mobile app.

What you get in the first 2 – 4 weeks

Since the speed ​​of validation is critical, in the first 2 - 4 weeks of working with Stubbs, you receive valuable technical and marketing insights:

• Visualized business logic: Mind maps and low-fidelity wireframes describing the architecture and key user journeys.
• Interactive design prototypes: Clickable, high-fidelity mockups, fully prepared for testing with real users or presenting to investors.
• A clear development plan: Technical strategy, PoC results, and a precise roadmap for building an MVP with a transparent budget.

Conclusion 

The development team needs to systematically eliminate risks that can undermine the success of the digital product they work on. A PoC ensures your core technology works, a prototype answers whether your users understand the interface, and a Minimum Viable Product proves that the market is actually willing to pay for your solution. If you skip these stages or confuse their purpose, it may lead to overspending and failed launches. If you understand the main differences and can choose the right method, the chances of success increase. The professionals from Stubbs can guide you from initial discovery to a flawless MVP launch. This way, you can protect your development cycle and build valuable products.