StartupsMVP and SaaS Development for Startups
Working MVP in 30 days. Core production build in 90. Built by in-house engineers who hand you a codebase you can extend rather than one you will have to replace.
TRUSTED BY TEAMS
Sodio builds MVPs, SaaS platforms and startup products, with a working MVP in 30 days and a core production build in 90 for a defined scope. We work as an in-house team of 35, so the engineers who scope your product are the ones who build it.
Before any commitment we produce a solution architecture at no cost — components, integrations, delivery phases and a costed plan — which is yours whether or not you build with us. We also assess AI feasibility before anyone commits budget to it, because most AI product ideas fail on data availability rather than on the model.
/// WHAT ACTUALLY GOES WRONG
Most MVPs Fail on Scope, Not Engineering
The Real Failure
The common failure is not that the build was bad. It is that the MVP was never minimum.
Scope Creep
A feature list agreed in week one grows through week four, the launch moves twice, and the product that eventually ships has cost three times the budget and answers no question the founder actually had. The discipline is deciding what to leave out, and that is a decision only the founder can make — but an agency that never pushes back is complicit in it.
Demo-Grade Code
The second failure is a codebase written to be demonstrated rather than extended. It works for the pitch, then has to be rewritten before the Series A build, which costs exactly the thing the MVP was supposed to buy — time. We write MVPs narrow but properly, so what exists can be built on.
AI Data Problem
The third is specific to AI products. An idea is scoped, a team is hired, and four months in it becomes clear the data needed to make it work either does not exist, is not accessible, or is too messy to ground against. That question is answerable in two weeks, and it should be answered first.
Timeline Honesty
And the fourth is timeline honesty. A 30-day MVP is achievable when the scope is agreed and decisions come back the same day. It is not achievable when the feature list is still moving. We say which case you are in before starting rather than in week three.
/// WHAT WE BUILD
What We Build for Startups
SaaS Development Services
MVP Development
MVP App Development
Hire MVP Developers
Startup Software Development
Startup App Development
Startup Web App Development
Enterprise MVP Development
Product Discovery Workshops
Prototype & Proof of Concept
Technical Due Diligence
///AI FOR STARTUPS
AI Products for Startups
Most AI product ideas fail on data availability rather than on the model. These pages exist to answer that question early, and then to build something that survives a technical diligence conversation.
AI MVP Development
An AI product demonstrable enough for funding or pilots, with evaluation built in rather than a thin wrapper over an API.
AI Feasibility Assessment
Whether the idea works with the data that actually exists. Finding out in week two costs less than finding out in month four.
AI Product Strategy for Founders
Where AI genuinely changes the product, and where it is a feature checkbox that will not survive contact with users.
LLM Integration for SaaS
Adding AI features to an existing product without rebuilding it — prompt management, caching, cost controls and fallbacks.
Data Readiness for AI
The pipeline before the model. Most AI ideas stall here, and it is almost never the part that gets scoped.
AI Demo & Investor Prototype
A working prototype that survives technical diligence in a funding round, not a scripted demo that breaks on the second question.
An AI product demonstrable enough for funding or pilots, with evaluation built in rather than a thin wrapper over an API.
Learn MoreWhether the idea works with the data that actually exists. Finding out in week two costs less than finding out in month four.
Learn MoreWhere AI genuinely changes the product, and where it is a feature checkbox that will not survive contact with users.
Learn MoreAdding AI features to an existing product without rebuilding it — prompt management, caching, cost controls and fallbacks.
Learn MoreThe pipeline before the model. Most AI ideas stall here, and it is almost never the part that gets scoped.
Learn MoreA working prototype that survives technical diligence in a funding round, not a scripted demo that breaks on the second question.
Learn More/// HOW WE WORK
From Idea to Production in 90 Days
Discovery — week 1
We establish what the product has to prove, who it is for, and which assumption carries the most risk. Scope gets cut here rather than negotiated later. If the idea needs data that does not exist, we find out now.
Free solution architecture
Components, stack, integrations, delivery phases and a costed plan, including what we recommend leaving out of version one. Yours to keep whether or not you build with us.
MVP — 30 days
One core loop, built properly, shipped to real users. Not a prototype and not a demo. Decisions have to come back the same day for this timeline to hold, and we will say so if they are not.
Production build — 90 days
The full product with payments, analytics instrumentation, monitoring and the integrations that matter. Written to be extended by your team or ours.
///ENGAGEMENT AND HANDOVER
You Own It, and You Can Take It
IP assignment
You own the code, the repositories and the IP. Assignment is written into the engagement, not negotiated at the end of it.
Handover
If you take development in house, you get repository access, documentation, architecture notes, deployment runbooks and a handover period with your team. No transition fee.
No lock-in
Engagements run on notice. The free solution architecture is yours to take to another firm if you would rather they built it.
You own the code, the repositories and the IP. Assignment is written into the engagement, not negotiated at the end of it.
Learn MoreIf you take development in house, you get repository access, documentation, architecture notes, deployment runbooks and a handover period with your team. No transition fee.
Learn MoreEngagements run on notice. The free solution architecture is yours to take to another firm if you would rather they built it.
Learn More///FEATURED CASES
Future-Proof Software for Your Business
At Sodio, we deliver mobile apps, web apps, blockchain (DApps), AI integrations, SaaS platforms, and custom software development. Our innovative solutions are scalable, secure, and user-friendly, designed to drive growth and efficiency, keeping your business ahead in the competitive landscape. Trust Sodio for your digital transformation needs.
Compliance Buddy
An all-in-one tax and regulatory compliance platform engineered to streamline GST returns, income tax filings, and corporate governance.
Munim App - Staff Management
A system designed to manage staff operations, payroll, and improve workforce efficiency.
Compliance Buddy
An all-in-one tax and regulatory compliance platform engineered to streamline GST returns, income tax filings, and corporate governance.
Munim App - Staff Management
A system designed to manage staff operations, payroll, and improve workforce efficiency.
/// FAQ
Frequently Asked Questions
It depends on how much you are willing to leave out. A genuine MVP — one core loop, one platform, no admin panel beyond what you need to operate — is a matter of weeks. Costs rise with multiple user types, payments, integrations, compliance requirements and AI features that need evaluation infrastructure. We give a costed breakdown during the solution architecture rather than a range that means nothing without scope.
For a defined scope, yes, and we have done it. The constraint is not engineering speed but decision speed — 30 days works when the scope is agreed and someone on your side can answer questions the same day. It does not work when the feature list is still moving in week two. Payment licensing, app store review and third-party approvals also sit outside our control, and we say which apply before starting.
You own it and we hand it over properly: repository access, documentation, architecture notes, deployment runbooks and a handover period with your new team. We write MVPs to be extended rather than replaced, because a codebase that has to be rewritten at Series A costs you the thing you were buying — time.
Yes to both. IP assignment is written into the engagement, not negotiated afterwards. We sign NDAs before discovery conversations where you need one.
With the data, not the model. Most AI ideas fail because the data needed either does not exist, is not accessible, or is not clean enough to train or ground against. An AI feasibility assessment establishes that in a couple of weeks and gives you a clear answer either way. We would rather tell you it does not work in week two than build toward it for four months.
Both, but honestly the fit differs. Funded companies can support a full product engagement. Pre-seed founders usually get more from a discovery workshop and a tightly scoped prototype than from a full build, and we will say so rather than selling a larger engagement. If a project is genuinely too small for us to add value, we will tell you that too.
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Learn More/// GET STARTED
Start With What to Leave Out
Tell us what the product has to prove and who it is for. We will come back with a solution architecture covering scope, stack, delivery phases and cost — including what we would cut from version one. No charge, and it is yours either way.