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How much does it cost to build an MVP: cost items, realistic timelines and what to postpone

Claudio — Tue, 03 Nov 2026 16:12:36 +0000

Anyone putting together a budget for a new digital product almost always ends up running the same search: how much does an MVP cost. The answers you find online range from a few thousand euros to more than one hundred and fifty thousand dollars, and taken at face value they don't help you decide anything.

The gap has a simple explanation. Eric Ries, who popularised the term, describes the MVP as the version of a product that allows a team to collect the maximum amount of validated learning about customers with the least effort. The definition is on the Lean Startup website, and it follows that the cost depends on what you leave out , far more than on the technology or the vendor's rates. If you have to present a figure to management at the start of the year, it pays to begin with the scope and only then ask for quotes.

The price ranges in circulation and how to read them

Almost all published estimates come from software houses, so they should be taken as orders of magnitude rather than independent statistics. For the Italian market, SystemForge puts the spend between €18,000 and €90,000, with timelines of 6 to 20 weeks, and places a simple MVP between €18,000 and €45,000, to be built in anywhere from six weeks to three months. A guide published on Il mio business plan goes as low as €5,000-20,000 for a working digital MVP.

International sources raise the bar. CMARIX and Resourcifi both cite a range from $15,000 to over $150,000; the latter adds that most projects wrap up in two or three months and that costs and timelines depend on scope more than on hourly rates. Softermii breaks it down by type: a simple MVP costs between $30,000 and $55,000 and takes 5-8 weeks, a standard SaaS needs $55,000-140,000 and 8 to 14 weeks of work, and a product with AI features runs from $140,000 to over $300,000 over 3-6 months.

What are the cost items of an MVP

Discovery

This is the part many people would like to skip, and it is also the cheapest. Its purpose is to put in writing who the users are, the hypothesis to test, the metric that will tell you whether it holds up and what stays out. A few hours of workshop are enough if the decision-maker is in the room; it stretches to weeks if every choice goes through three meetings. The resulting document protects both sides, because every feature added verbally during development becomes a budget change.

UX and UI

Wireframes, interface design, a couple of review rounds. The cost grows with the number of screens and with the states of each one (empty list, error, loading), which are often missing from quotes and then reappear once the project is under way. For an MVP, a polished design built on standard components works well: the brand comes through, and custom animations can wait.

Development

This is the heaviest item and the one that varies the most. It covers sign-up and login, the core features and the admin panel for managing users and content. The admin panel is often underestimated: without one, every data correction goes through the developer and costs keep rising even after launch. When the product has to run on iOS and Android, a cross-platform framework such as Flutter or React Native lets you write a single codebase instead of two.

Integrations

Payments, transactional emails, maps, AI models. Every connection has a development cost and a usage cost. Well-documented APIs, such as those from Stripe, email delivery services or OpenAI and Anthropic, can be integrated in predictable timeframes. A corporate ERP or an outdated management system is another story: sparse documentation, data that needs cleaning, test environments that sometimes don't exist.

Infrastructure and recurring costs

This covers the expenses that continue after delivery and that are best budgeted from the start: hosting, domain, third-party services. A mobile app requires developer accounts. The Apple Developer Program costs $99 per membership year, while Google Play Console charges a one-time fee of $25. If you take payments online, every transaction carries a percentage fee plus a fixed amount (current rates are on Stripe's pricing page). AI features add API usage, which grows along with your users: at MVP stage the figures stay modest, but it should be monitored from day one.

A practical tip: have hosting, domain and accounts registered in your company's name, not the vendor's. The day you want to switch partners, it will save you a lengthy handover.

Testing and acceptance

Manual testing of the main flows, checks on real devices, bug fixing, acceptance testing with the people who will use the product. In a six-week project, dedicating one week to this phase is a reasonable proportion. Also ask how long the post-release bug warranty lasts, because the strangest problems surface when real users arrive.

Realistic development timelines

For a small, well-defined scope, six weeks is a sustainable timeframe, in line with the lower end of the estimates above. This is the schedule we follow in our projects:

Week 1: analysis and wireframes.
Week 2: design, with two review rounds.
Weeks 3 and 4: feature development.
Week 5: admin panel and testing.
Week 6: acceptance testing and release.

A demo at the end of each week lets whoever commissioned the work see the real state of the product and correct course before a wrong choice becomes expensive. When deadlines slip, the cause is rarely technical. The reasons we see most often are late decisions, content (copy, images, test data) delivered after development has started and features added halfway through. That is why, before signing, it's wise to name one person who can approve screens within a day or two.

Three scope examples: B2B portal, Flutter app, AI SaaS

The examples below are hypothetical, but they reflect the kind of requests we receive. They show how the cost changes as screens, features and platforms vary.

B2B portal for reseller orders

A component distributor wants to find out whether its resellers would order online rather than by email and phone. The MVP includes a private login, a catalogue with a dedicated price list, a cart with order submission and order history. There is a single integration, confirmation emails. The admin panel lets the sales office enable accounts and see what comes in. The metric to set during discovery could be the share of orders received through the portal in the first two months from a pilot group of customers.

Left out are automatic ERP synchronisation (at first the price list is uploaded from a file), multiple discount tiers and the mobile app. We're talking about eight screens and three core features: it's the smallest scope of the three and sits below the lower end of almost every market range.

Flutter app for booking classes

A chain of sports centres wants to test an app for booking classes. It needs a web application for staff and an app for customers, published on the App Store and Google Play and written in Flutter to have a single codebase. There are five features: class calendar, booking with cancellation, membership with online payment, user profile and QR code check-in. Integrations go up to two (payments and push notifications for reminders) and so do the roles, instructor and customer, for a total of around fifteen screens.

A loyalty programme, chat with instructors and statistics for management wait for phase two. Compared with the portal, the cost roughly doubles, because features, interfaces and platforms increase, and developer accounts and store review times come into play.

SaaS with an AI feature

A consulting firm wants to sell other firms a service that reads uploaded contracts and extracts deadlines and key clauses. The heart of the product is a single feature: document upload, extraction through an LLM from OpenAI or Anthropic, human review of the result, export. Around it you need sign-up, account management and a subscription.

Market estimates for AI MVPs are the highest, as we saw with Softermii. To validate an idea like this, though, you rarely need to train anything custom: an existing model called via API, a carefully crafted prompt and a screen where the user corrects the output are enough. That keeps the cost close to a web MVP with one integration, plus API usage. If the product generates content or interacts with people, also check the transparency obligations under the AI Act.

What to postpone without undermining validation

Spending little doesn't achieve much if the starting hypothesis is wrong. A CB Insights analysis of 101 startups, cited by DigitalOcean, identified the lack of a market need as the cause of failure in 42% of cases. If the hypothesis isn't clear yet, it's worth going through a market testing phase before asking for quotes, as we explained when discussing how to validate a digital product before building it.

The rule we use for cutting is this: a feature goes into the MVP only if you can't measure the hypothesis without it. Everything else waits for the data collected from users. These are the items that most often end up on the postponement list.

The second platform: if your audience works at a desk, start with the web; if they're on the move, go for a mobile-optimised web version or a single app.
Store publication, when the web version is enough to gather initial feedback.
Push notifications and marketing automation.
Granular roles and permissions: at first, user and administrator are enough.
Full integration with ERP and management systems, which can be replaced for a few months by a file import.
Advanced reports and dashboards, when a CSV export is sufficient for the chosen metric.
Multiple languages, customisable themes, animated onboarding.
Optimisations for traffic volumes you don't have yet.

Some things, on the other hand, are worth investing in from the start. Login and data security, legal requirements (privacy and, if you fall within its scope, the European Accessibility Act) and a minimum of analytics to read the agreed metric. An MVP without usage data is cheap, but it leaves the same questions open as before.

How we set up an MVP at DevInterface

For MVP development we chose a fixed scope at a locked price, and that is what allows us to stay below almost all the ranges above. The Web or Mobile MVP costs €5,000 + VAT and is delivered in six weeks. It starts with a two-hour workshop that produces a Technical Annex listing users, hypothesis, success metric and what stays out. It then includes up to eight pages with your brand, sign-up and login, up to three core features, one integration of your choice among payments, email, maps or AI, the admin panel and a 60-day bug warranty.

The MVP Plus costs €10,000 + VAT, with the same timeline. It adds smartphone apps published on the stores to the web app, goes up to five features, two integrations and fifteen screens, handles multiple user roles and push notifications, and covers bugs for 90 days. In both cases you pay 40% at kickoff, 30% at the midpoint and 30% on acceptance, and the code and rights pass to you on final payment. Hosting, domain, developer accounts and AI service usage remain in your name and at your expense, as we recommended earlier. After launch you can continue with monthly sprints at €5,000 + VAT, up to 80 hours, deciding new features based on the data collected.

Applied to the three examples, the B2B portal fits the first plan and the class booking app the second. The AI SaaS fits the base plan if subscriptions are activated manually in the first few months, while automatic payment requires the second integration included in Plus.

Before talking to us or anyone else, write down on a single page the hypothesis, the metric and the three features without which you can't measure it: with that page in hand, quotes become comparable.

Three products, one approach to software: ConSergio, Widgeto and Kleio

Claudio — Tue, 03 Nov 2026 16:11:36 +0000

Some questions arrive at the least convenient moment. A guest needs directions to their accommodation after reception has closed; a prospective customer looks for a detail on a website and cannot find it; a small business has to piece together the history of an enquiry before preparing a quotation. These are different situations, but they have something in common: the information exists and the next step is clear, yet friction between a person and the answer takes up time and attention.

DevInterface develops bespoke software for businesses with different needs. Alongside this work, we have three products of our own: ConSergio, Widgetoand Kleio. This year, we want to bring them to a wider market. The best way to introduce them is to start with the practical problems each one aims to solve.

They are three distinct products. The thread running through this article is one way of looking at them together: technology can make knowledge easier to access, help a conversation get off to a good start and give continuity to the work that follows. Each product addresses a different part of that journey, for its own users and setting.

ConSergio: hospitality continues when reception is closed

Anyone running a hotel, B&B or agritourism business knows the value of an answer at the right moment. For a guest, finding out how check-in works, what services are available or where to go during a stay can mean the difference between a smooth experience and a frustrating search through messages, web pages and documents. For the property, the same questions often come up repeatedly, sometimes in different languages and outside the hours when staff can reply straight away.

ConSergiois designed for this situation. It is a digital concierge for accommodation providers that can answer guests in multiple languages at any time. Its role is to make useful information available when it is needed, ease the burden of recurring enquiries and give staff more time for matters that call for their attention, judgement and care. Hospitality remains a human relationship; a well-designed digital tool can help it run more smoothly, particularly when a wait or a hard-to-find answer might otherwise interrupt it.

ConSergio shows the value of designing for a specific setting. As well as answering questions, it can collect requests, help guests book services and pass matters requiring a person to the staff. An assistant for hospitality has to fit the rhythm of a stay, guests’ needs and the daily work of those who welcome them.

With the Reservations module, ConSergio can also manage rooms, availability and stays and, on supported plans, collect booking requests directly from the property’s website. Online pre-check-in also allows guest details to be collected in advance, simplifying check-in and preparing information for the property’s mandatory guest reporting requirements.

Widgeto: making a website a place to ask questions

A business website can hold answers to countless questions and still leave a visitor unable to find the one they need. Information is spread across pages, service descriptions and documents. Finding the relevant detail takes time, especially for someone encountering the business and its terminology for the first time. Even a well-organised site cannot anticipate every question: sometimes people simply need to ask in their own words.

Widgetobrings that option into the website. It is an AI chatbot that uses the contents of web pages and documents to answer visitors’ questions. The aim is to bring what a business knows closer to what a customer wants to understand, making existing information easier to access. This can help someone exploring a service, weighing up options or seeking clarification before getting in touch.

The question is whether that conversation genuinely helps visitors find their way and helps the business communicate more clearly. In our article about moving from features to value, we explored this distinction: a new feature matters when it improves a real experience. Widgeto offers a way to apply that question to a place where many businesses first meet their customers.

Kleio: keeping work moving after the first contact

A clear answer can start a relationship, but someone then has to carry it forward. An enquiry becomes a conversation; that conversation might lead to a quotation and, if things go well, a sale. For many small and medium-sized businesses and craft enterprises, this journey crosses different people, tools and documents. When information is scattered, recovering the context and working out what has happened so far takes effort away from the job itself.

Kleioaddresses this part of the process and what follows it. It is a modular business management platform that connects customers, quotations, orders and projects, with modules covering sales, purchasing, tasks, staff, stock, accounting and documents. DevInterface also presents it as a solution for SMEs and craft businesses. Its modular structure matters because businesses do not all start in the same place and can choose a configuration that suits their workflows.

A process does not improve simply because it moves onto a screen. Its stages and the people involved need to be understood. This is close to a theme in our article about DevInterface’s development process, and helps explain Kleio’s proposition: bringing information and activities that might otherwise remain separate into one environment.

The link between the products lies in people’s journeys

ConSergio, Widgeto and Kleio work in different areas. One supports guest services at accommodation providers; another helps people visiting a website to ask questions; the third helps businesses organise their commercial and operational work. Looked at together, though, they suggest a sequence familiar to many organisations: someone looks for information, starts a conversation and expects that conversation to lead somewhere in an orderly way.

That is the connection this article draws between them: a shared view of people’s needs, without assuming that the three platforms are technically integrated. Making information easier to find, providing answers when they are useful and keeping subsequent work organised are different but related goals. Each product tackles one of them with its own identity and intended users.

In our account of 2025 we shared our work on client projects and our exploration of new solutions. Introducing these three products is part of that story. It also opens a phase in which listening to users, gathering feedback and continuing to develop the products will matter.

It is a way of showing the spirit of DevInterface, too: an interest in technology and in the point where it meets people’s work, from a guest who needs to find their way to a visitor looking for an answer and a business seeking to manage its activities more effectively. To find out more about ConSergio, Widgeto and Kleio, visit their websites. If any of the frustrations we have described sound familiar in your organisation, we would be glad to talk.

Which process to automate first with AI: an 8-question checklist for businesses

Claudio — Tue, 03 Nov 2026 16:07:18 +0000

In 2025 the share of Italian companies with at least 10 employees using artificial intelligence doubled, from 8.2% to 16.4%, according to the Istat report Imprese e Ict 2025. The gap by company size remains wide: AI has reached 53.1% of businesses with at least 250 employees and 15.7% of SMEs. The most telling figure, however, is a different one. A third of the companies adopting it (33.4%) report no business purpose at all, and 83.3% of these are small firms with 10 to 49 people, as Key4biz sums up.

So many companies are trying out tools before deciding where to use them. Meanwhile the market is moving fast: according to the Osservatorio Artificial Intelligence at Politecnico di Milano, it grew by 50% in 2025, reaching 1.8 billion euros. The eight questions below are for people who run operations, finance or IT and need to choose the first process to automate without burning the budget on a pilot that nobody ends up using.

Start with the problem

The authors of the analysis published by Key4biz, Gambaro and Lo Turco, suggest starting from a specific business problem and dropping the vague goal of "adopting AI". Their examples are very concrete: preparing a quote faster, predicting a breakdown, reducing waste, planning orders better, eliminating repetitive manual tasks.

They also describe where they struggled most. Choosing the tool mattered little; the real work was mapping processes, improving data quality, assigning responsibilities and getting different skill sets to work together. This matches our experience, because when we assess an AI workflow with a company, much of the time goes into understanding how the process works today, exceptions included.

To use the checklist, pick three candidate processes. They could be sorting the emails that land in the general inbox, entering supplier invoices into the management system and preparing quotes. Then ask yourself the same questions for each of them.

The 8 questions to assess a candidate process

1. Volume and repetitiveness

Automating business processes with AI pays off when a task recurs often and follows similar rules. An info@ inbox that receives hundreds of messages a week, each of which has to be read and forwarded to the right department, is an excellent candidate: an LLM classifies the request, extracts the useful data (customer, order number, urgency) and routes it. The quarterly report that takes the controller two days of thinking is a much weaker one. Count how many times the task comes up in a month and multiply by the minutes it takes: that gives you the hours at stake.

2. Data quality and access

This is where the starting questions proposed by Gambaro and Lo Turco come in handy: what data do we have, where is it, who produces it, how reliable is it, and can we connect it. Scarce or poor-quality data also appears among the obstacles reported to Istat by companies that considered AI without adopting it.

With documents the start is usually easy, because current models can read invoices, delivery notes and orders even from scans. Quotes are a different matter. You need up-to-date price lists, discount rules and a history of past offers, which often lives in scattered Excel files or in the memory of your most experienced salesperson. The same authors note that a lot of useful information sits in people's experience and in no database at all.

3. Integration with ERP and management systems

An AI agent that reads an invoice and leaves a person to retype it into the management system saves very little. The gain comes when the data flows into the ERP, CRM or ticketing system on its own. Check whether your system exposes documented APIs, accepts file imports or at least has a reachable database. With a closed, outdated system the integration can cost more than the AI part, and at that point it is worth looking at the signs that it is time to replace your management software.

4. Cost of errors

Every model gets things wrong some of the time, so the useful question is about the consequences. An email sent to the wrong department is fixed with a forward. A wrong amount in a quote that has already gone out, or an incorrect VAT rate in the accounts, costs far more. For your first projects, choose processes where errors are recoverable, or build in a human approval step : the agent prepares the draft, and the operator checks and confirms it.

5. Measurable KPIs

If nobody knows today how long a task takes, tomorrow it will be impossible to say whether AI has shortened it. Before you start, set two or three indicators and measure them on the current situation: average response time to a request, minutes to record a document, quotes completed per week, share of manual corrections. That 33.4% of companies with no stated purpose, which Istat reads as a sign of adoption that is still experimental, is exactly the situation to avoid.

There are some figures on expected results. A Banca d'Italia study from March 2026 (Ropele and Tagliabracci), reported by Key4biz, links AI adoption to a 5.2% increase in value added per employee and an 11.9% increase in gross operating margin per worker. The sample covers companies with at least 50 employees, and adoption is self-reported by the companies. These figures should therefore be read as a trend, and they may look very different for, say, a 15-person company.

6. People involved

Lack of skills is the main obstacle cited by those who considered AI and then gave up, accounting for 58.6% of responses. A project needs at least three roles: someone who knows the process in detail, someone with the authority to make decisions and someone who will use the tool every day. Involve the people who do the work by hand today right from the analysis phase, because they know the exceptions and shortcuts that no written procedure records.

7. Regulatory constraints

Regulatory uncertainty and privacy are two more obstacles in the Istat survey. Personal data of customers or employees, decisions that affect people and regulated industries all lengthen timelines and require checks with the DPO or legal counsel. The AI Act treats some of these uses as high risk, with heavier obligations; for disclosure obligations towards users, you will find practical examples in our article on the AI Act and transparency obligations for tech and marketing. As a first project, an internal process is simpler: one based on non-sensitive company data, where AI prepares the work and the decision stays with a person.

8. Time to a prototype

The last question is about speed: how many weeks will it take before you see the system working on your real data. A good first candidate produces a usable prototype in 2-4 weeks, the same timeframe we set for prototypes in our AI consulting projects. If you need six months of data cleanup and three integrations before getting anything, that process should be tackled later, once the team already has a successful project behind it.

A scorecard to rank your processes

Give each candidate process a score from 1 to 5 for each question, where 5 always means the situation most favourable to automation. A spreadsheet with one row per process and one column per criterion is more than enough.

Volume and repetitiveness: 1 if the task comes up a few times a month, 5 if it recurs every day with stable rules.
Data: 1 if the information is scattered or in people's heads, 5 if it is digital, organised and accessible.
Integration: 1 if the management system is closed, 5 if it has ready-made APIs or imports.
Cost of errors: 1 if a mistake reaches the customer or the accounts, 5 if it can be fixed in a few seconds.
KPIs: 1 if you measure nothing today, 5 if you already have baseline times and volumes.
People: 1 if there is no owner, 5 if you have a process lead and users willing to try.
Regulatory constraints: 1 for sensitive data or decisions about people, 5 for internal, non-personal data.
Time to prototype: 1 if months of preparation are needed, 5 if you can test within a month.

The maximum score is 40. As a rule of thumb, above 30 you have a strong candidate, between 20 and 30 a process that needs some groundwork (usually on data or integration), and below 20 a project to postpone. If two processes end up close, look at the scores for data and for the consequences of errors, which carry more weight than the others in a first project.

In our example, email triage scores high on volume, severity of errors and time to prototype. Quotes may be worth more financially, but lose points precisely on data and errors. It makes sense to start with the first and move on to the second with a few months of experience and a cleaner history.

From score to first prototype

Once you have chosen the process, write a one-page brief before talking about models or vendors.

Describe the process as it works today, with its steps, the systems involved and recurring exceptions.
Record the baseline KPIs measured over at least three weeks.
List the data sources and who is responsible for each.
State who approves the agent's output and in which cases a person steps in.
Set the date by which the prototype will be evaluated and the minimum result needed to continue.

With this brief in hand, the conversation with a vendor or with your internal team shifts to your process and your numbers. If your company lacks a technical figure who can lead the project, a Fractional CTO can fill that role part time.

If you would rather do this work together with us, you can start with DevInterface's free AI assessment. We take the processes you have identified, assess them against your data and systems, and point out the one that makes the most sense for building your first prototype.