Engagement 03
3+ weeks · ₹3,00,000+
Full Product Build
Zero to one AI SaaS. Full stack, fixed scope.
When the MVP shape is clear and you need a real product: accounts, roles, AI features, admin, and a deploy your users can live in — not a prototype that falls over on day two.
Full-stack AI SaaS product
- 01
A multi-user product with auth and core AI features live
- 02
Admin and operator paths so you can support customers
- 03
A codebase structured to keep shipping after handoff
Best for
- 01Seed / Series A teams with a validated product idea
- 02Technical founders who want speed without a thin wrapper
- 03Teams graduating from a successful MVP into a sellable product
Out of scope
- Large multi-department ERP or data platforms (see Enterprise Platform)
- App-store mobile native apps unless explicitly scoped
- Ongoing growth marketing, SEO campaigns, or content production
- Open-ended feature backlog without milestone gates
What you get
Product foundation
- Auth (sign-up / login), sessions, and basic roles
- Core product UI for the primary user journeys
- Data model and API layer for the scoped features
AI-native layer
- AI features wired into the product flow (not bolted on as a chat toy)
- Guardrails: rate limits, cost controls, failure states
- Logging and basic eval hooks for the model path
Ops & handoff
- Admin or internal tools for support and configuration
- Production deploy, env management, and monitoring basics
- Documentation: architecture, runbook, and how to extend
Scope of work
- 01
Product spec
We lock journeys, roles, and AI surfaces before the sprint — so “full product” does not mean infinite scope.
- User roles and primary flows
- AI feature list for v1 vs explicit later
- Integrations required at launch (CRM, email, storage, payments hooks)
- 02
Build sprint
Full-stack implementation with weekly demos and a shared Linear board.
- Frontend + backend + AI pipeline
- Auth, permissions, and admin paths
- QA against acceptance criteria in the spec
- 03
Launch readiness
Ship to production with enough ops surface to support early users.
- Deploy + smoke + handoff
- Support notes for common failures
- Path into maintenance for model and feature iteration
How it runs
I
Discovery
Roles, journeys, AI surfaces, constraints.
II
Spec + quote
Fixed scope, milestones, and price.
III
Build
Full-stack sprint with weekly reviews.
IV
Launch
Production deploy, docs, optional retainer.
Payment
50% upfront, 30% at milestone, 20% on delivery.
- 01
50%
Upfront
Due to start the build
- 02
30%
Milestone
Due at the agreed mid-build checkpoint
- 03
20%
Delivery
Due on ship and handoff
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Other engagements
Ready to scope this?
Tell us the workflow, constraints, and timeline. We’ll come back with a written plan.