AI product development: MVPs, SaaS and GenAI Build what’s missing, AI-native from day one.

MVPs, platforms and GenAI features for startups, SaaS companies and PE portfolio companies, built by a Sprint Pod that ships tested software every two weeks.

Sprint 6 of 6 MVP readyweek 12, on the date agreed
Sprint reviewFriday
Shipped this sprint
14stories done · 0 open critical bugs
Demo: document upload, extraction and the first scoring screen, live on staging.
Illustrative data
Who it’s for

Teams that need to ship, not hire.

Startups

An MVP in weeks, fast roadmap execution, and full-stack delivery while you raise and find product fit.

SaaS companies

Feature acceleration, onboarding, integrations and GenAI features without stretching your core team.

PE portfolio companies

Post-deal acceleration, cost takeout and delivery continuity across a portfolio.

What we build

From first version to platform.

AI-native MVPs

A working first version, built around the AI from the start rather than bolted on later.

GenAI features

Search, assistants, document extraction and agents, inside the product you already have.

Data platforms

Secure pipelines, vector databases and multi-tenant architecture that hold up under real volume.

SaaS platforms

Admin, billing, roles and access controls, ready for more customers and enterprise buyers.

Mobile and web apps

Customer-facing apps and storefronts, with the backend that keeps them running.

Replatforms and rebuilds

Take over a codebase you’ve outgrown and move it to something that scales.

How we build

Working software every two weeks, from the first sprint.

  1. 1

    Frame

    Agree the problem, the users and what “done” means.

  2. 2

    Design

    Flows, architecture and the riskiest parts first.

  3. 3

    Build in sprints

    A demo of working software every two weeks.

  4. 4

    Launch

    Harden, test and ship to real users.

  5. 5

    Scale

    Grow the Pod or hand over, as you prefer.

A typical 12-week MVPIllustrative
Frame & designweeks 1–2
Sprint 1core flow
Sprint 2AI model in
Sprint 3roles, admin
Sprint 4integrations
Launchharden, ship
Our work

Built, shipped and running.

AI underwriting MVP

A Sprint Pod acted as Cadastral’s product team and took an AI underwriting product from idea to a working MVP.

  • MVP in 12 weeks
  • Built AI-native from the first sprint
Torno was more than an engineering partner. They were my product team from day one. Aman · Co-founder, Cadastral AI
Data platform · investor-backed

A secure, modular platform for high-volume data ingestion, embeddings and multi-tenant use, delivered against tight compliance and go-to-market deadlines.

  • Secure pipelines and vector databases
  • Admin dashboards with strict access controls
  • Ready for a multi-tenant rollout
Torno gave us delivery continuity with better cost control than any of our previous partners. Andrew · Investor Partner, DAIS
Quick-commerce app

A grocery app and web platform for residents of multi-family buildings, built from scratch for a Chicago startup with no product or tech team.

  • Mobile app, storefront, cart and checkout
  • Real-time ordering and delivery tracking
  • Ready to onboard more buildings and vendors
Torno didn’t just execute tasks. They partnered with us in building the product from day one. Aasim · Founder, Crateful
Why teams pick a Pod

Speed, accountability and a team that feels in-house.

Shipped every two weeks

Working software at the end of every sprint, inside your tools and rituals.

AI-native engineers

Engineers who have shipped real GenAI, ML and data-heavy products, not demos.

Onsite when it matters

Key Pod members come onsite for launches, stakeholder alignment and fast iterations.

Every engagement is run by a Sprint Pod. How Sprint Pods work →

FAQ

Questions we hear first.

How fast can a Pod start?

Pods typically ramp in under five days.

How long does an MVP take?

It depends on scope. Cadastral’s AI underwriting MVP took 12 weeks, with a demo of working software every two weeks along the way.

Can you take over an existing codebase?

Yes. We start with a short review, stabilize what’s there, and then keep shipping.

Will you work with our in-house team?

Yes. The Pod works in your tools, your time zone and your rituals, and can pair with your engineers.

How do you price?

A fixed price for a defined scope, a retainer once we’re past framing, or a mix of the two. For the right early-stage company, we’re open to investing alongside.

Can we scale the team up or down?

Yes. Specialists such as architects, AI/ML leads and DevOps join from a shared flex layer when needed.

Start here

Bring us what you need built.

A first version, a new feature or a platform you’ve outgrown. Pick one, or tell us yours.

  1. 1
    A 30-minute callWe learn what you’re building and why.
  2. 2
    A clear planScope, team and the first two sprints.
  3. 3
    A Pod in daysWorking software from the first sprint.