From idea to live product in 6–10 weeks.
We build full-stack AI-powered SaaS products end to end — product strategy, UI/UX design, engineering, infrastructure, and go-to-market. You get a production-ready platform, not a prototype.
Everything you need, nothing you don't.
Each engagement is scoped to what you actually need. No upselling, no bloat.
MVP in 6–10 Weeks
Scoped, designed, built, and launched. We move fast without cutting corners on architecture.
AI-native Architecture
LLM integration, embeddings, and AI feature layers designed in from day one — not bolted on later.
Multi-tenant & Billing
Workspace isolation, role-based access, subscription management, and Stripe or Razorpay integration.
Scale-ready Infra
AWS or GCP deployment with autoscaling, managed databases, CDN, and zero-downtime deployments.
Product Strategy & Design
User research, wireframes, and a full Figma design system before engineering starts.
Ongoing Product Partnership
Post-launch retainer option for feature development, infra management, and growth engineering.
Simple steps. Clear outcomes.
We keep the process lean so you spend less time in meetings and more time seeing results.
Strategy & Scoping
We define the product, prioritise features for the MVP, agree on the tech stack, and lock the timeline.
Design & Engineer
Design and engineering run in parallel sprints. You get weekly demos and a staging environment from week one.
Launch & Grow
We handle production deployment, monitoring setup, and stay on to ship the next iteration.
How it plays out in practice.
A real-world scenario from start to finish — the kind of outcome we build toward.
PGenius: an AI PG-management platform, zero to live in 8 weeks
A founder had validated demand for an AI-powered platform to manage PG accommodations but needed a production-ready, multi-tenant product — not a prototype — fast enough to capture the market.
We ran a one-week strategy and scoping sprint, then design and engineering in parallel: multi-tenant architecture, role-based access, automated rent collection, AI tenant onboarding, an occupancy dashboard, and billing — with a staging environment from week one and weekly demos.
PGenius went from idea to a live, production platform in 8 weeks and now serves property managers across India, with us continuing as the product partner for new features.
Seen it work across industries.
These are the kinds of problems we've solved — and the results they produced.
PGenius — PG Management Platform
Built India's first AI-powered PG accommodation platform from zero to live in 8 weeks, now serving property managers across India.
AI Document Processing Tool
Multi-tenant SaaS for contract review and extraction, launched with full billing, team workspaces, and an LLM analysis engine.
Talent Matching Platform
Two-sided marketplace with AI-powered candidate ranking, employer dashboards, and automated interview scheduling.
Questions about saas platform development.
The things prospects ask us most. Still unsure? Book a free call and ask us directly.
Can you really build a SaaS MVP in 6–10 weeks?
Yes, for a well-scoped MVP. We lock the feature set in a strategy phase, run design and engineering in parallel sprints, and give you a staging environment from week one. The 6–10 week range covers a production-ready first version, not a throwaway prototype.
What tech stack do you build on?
We use modern, well-supported stacks — typically React/Next.js on the front end, Node or Python services, Postgres, and AWS or GCP — chosen so you can hire for and maintain the product long after launch.
Do you handle billing, authentication, and multi-tenancy?
Yes. Workspace isolation, role-based access control, subscription management, and Stripe or Razorpay billing are built in as part of the platform, not bolted on later.
Who owns the code and the infrastructure?
You own everything — the codebase, the cloud accounts, and the IP. We can manage infrastructure for you on a retainer, but you are never locked in.
What happens after launch?
Every build includes a post-launch support window. Most clients continue on a retainer for feature development, infrastructure management, and growth engineering as the product scales.