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

01

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
02

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
03

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

  1. 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)
  2. 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
  3. 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

  1. I

    Discovery

    Roles, journeys, AI surfaces, constraints.

  2. II

    Spec + quote

    Fixed scope, milestones, and price.

  3. III

    Build

    Full-stack sprint with weekly reviews.

  4. IV

    Launch

    Production deploy, docs, optional retainer.

Payment

50% upfront, 30% at milestone, 20% on delivery.

  1. 01

    50%

    Upfront

    Due to start the build

  2. 02

    30%

    Milestone

    Due at the agreed mid-build checkpoint

  3. 03

    20%

    Delivery

    Due on ship and handoff

Related work

Other engagements

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