A data-driven approach to model an in-demand product that includes business analysis, proof of concept (POC), design concept, and project estimate.
A data-driven approach to model an in-demand product that includes business analysis, proof of concept (POC), design concept, and project estimate.
A complex human-centered process of developing a valuable product that blends business goals and user needs with design thinking in mind.
Narrow scope, single user flow, no integrations.
We use no-code and AI prototyping tools to validate your hypothesis at minimal cost.
Core feature set, one user role, basic auth and deployment.
AI-enabled engineering workflows handles repetitive code so your budget goes toward the features that prove market fit.
Multiple user roles, billing, permissions, dashboards.
We use human-led, AI-assisted code review to catch costly architecture mistakes early before they compound.
Everything in the MVP tiers plus user permissions, compliance-ready security, integrations with external services, and a team that ships new features every week.
Team uses AI tools to handle testing and code generation so delivery stays fast without growing headcount.
Before a single sprint starts, AI agents help us design the feature architecture, surface logical gaps, and cover non-functional requirements upfront. This alone eliminates the biggest invisible cost in any project - gaps that cause rework. We find them before development begins.
We design wireframes and prototype with AI-generated layouts to explore more options faster, and validate the experience with real users.
Following a structured plan, AI agents iteratively make changes to the codebase. The conversion from requirement to working code is now multiple times faster than manual coding. This is where the impact is largest and where your budget savings are most visible.
Every pull request goes through two layers. First, an AI agent reviews the code against a predefined instruction set, filtering out 70–80% of issues before they reach a human. Then our Engineering Manager validates and signs off. Faster cycles, fewer back-and-forths, same standard.
We use AI agents both for writing test suites and for accelerating manual QA of complete features. Higher test coverage without increasing time or cost.
We set up monitoring, handle deployment, and stay available for the post-launch period when real users find things no testing environment catches.
Best for simple, well-defined tasks when you have technical oversight. You become the PM, QA, and integrator.
You pay for hours.
Upfront cost
Low ($25–$120/hr), the entire management is on you.
Best for startups and SMBs that need a full team from day one. Quick team setup and wide range of expertise.
You buy results.
Upfront cost
60% faster delivery than freelancers and ~30% cheaper than in-house. No overhead of hiring, onboarding, or managing.
Best for companies post-PMF that need long-term ownership.
Slow hiring and shipping before the team is ready.
Upfront cost
High. $120K–$220K/year per senior engineer. Long runway needed
We are not attached to a particular technology stack. We solve your business challenges using the most fitting programming languages and frameworks.
The cost depends on product type, scope, and how well-defined the requirements are before development starts. A basic web app MVP runs $15,000–$30,000. A SaaS platform starts around $30,000–$80,000. A full-featured SaaS product typically starts at $80,000 and scales from there. At Uinno, AI-assisted development means budgets that used to be $40–60K now land in the $20–30K range for the same scope. We run a paid Discovery Phase before development begins, so you get an accurate, scoped estimate rather than a number pulled from thin air to win the deal. No surprises when the invoice arrives.
Yes, and it's often where we add the most value. We'll audit the existing code with the help of AI-assisted analysis to spot inefficiencies faster than a manual review alone, then tell you honestly what's worth keeping and what isn't. We won't recommend scrapping everything just because it's not ours. If incremental improvements will get you to launch faster, that's the recommendation you'll get.
We use fixed-scope sprints, so every two weeks you know exactly what's being built and what it costs. If your needs change, and they often do, we scope the change before we start it. You'll never get a surprise invoice for work you didn't explicitly agree to. If a change affects the timeline or budget, we have that conversation before it affects either.
Yes, and we plan for it from the start if you tell us that's the goal. Documentation, code structure, and onboarding support are part of the handover. We've done this multiple times. Founders who launch with Uinno raise a Series A, then start hiring their first in-house engineers.
Startups are our focus because our process is built for speed, budget constraints, and uncertainty. But we also work with growth-stage companies that need to ship new products fast or modernize existing ones. If you need to move quickly and can't afford to wait six months for results, we're a good fit.
you have a vision
