From first call to production.
No mystery. No black box. Here's exactly what happens when you work with us, who's involved at each step, and what you can expect.
Discovery Call
30 minutes · Venkat or Dharini · Free
You tell us the problem. Not the solution, not the architecture, not the tech stack. The problem your users have.
We ask five questions: What problem are you solving? What does your data look like right now? What does "working" mean to you? What's the accuracy threshold? What systems does this need to connect to?
By the end of the call, we know if we can prototype it in 72 hours. If we can't, we'll tell you. If we can, we scope the prototype and start.
What you get: A clear yes/no on whether we can help, a rough prototype scope, and honest expectations on timeline and cost.
72-Hour Prototype
3 days · 2-3 engineers + PM
Working code. Real AI. Running on a staging environment you can interact with. Not a mockup, not wireframes, not a slide deck.
The prototype proves one thing: does this approach work for your use case? We scope it to the core hypothesis. If you're building a document Q&A system, the prototype answers questions from your actual documents. If you're building a compliance tool, it processes a real sample of your data.
At the end of 72 hours, you see it running. Then you decide whether to move to a full build.
What you get: A working demo on a staging URL. Real AI processing your data. A clear answer on whether the approach is viable.
Sprint Build
2-week sprints · Dedicated pod + PM
Production-grade development in 2-week sprints. Each sprint has three goals, stated as outcomes, not tasks. "By end of sprint, a logged-in user can export results as a PDF with citations" — that level of specificity.
Your pod is a dedicated team: engineers matched to the project's needs (AI, frontend, backend), supervised by a technical PM who's your daily point of contact.
What happens during each sprint:
- Day 1: Sprint planning. PM, pod, and you align on three outcomes.
- Days 2-9: Engineering. Daily async updates in your shared channel.
- Day 10: Live demo. You see every feature running on staging.
- After demo: Handoff document within 2 hours. Five sections: what shipped, what changed, what's next, blockers, decisions needed.
What you get: Working software at the end of every sprint. A handoff document you can share with your team. No surprises.
Production Deploy
Handoff + optional ongoing support
We deploy to your infrastructure or ours (Cloudflare Workers, AWS, GCP — your choice). Full documentation, environment setup guides, and a clean Git repo you own completely.
After launch, you can either take over entirely (the codebase is yours) or keep a pod for ongoing development. Several clients start with a fixed-bid project and transition to a monthly pod for continued feature work.
What you get: Production deployment, full documentation, clean handoff. You own the code.
How we keep the bar high.
Every project reviewed by our CTO
Anil Gulecha (ex-HackerRank, ex-Google) reviews architecture decisions, model selection, and code quality on every project. Not as a formality. He's the one who decides between pgvector and Pinecone, whether a task needs RAG or fine-tuning, and whether the code is production-ready.
Your data stays your data
NDAs signed before any data is shared. Client data is processed in isolated environments. We never use client data to train models or share it across projects. When the project ends, your data is deleted from our systems.
You own everything we build
Full IP transfer. Clean Git repos. No proprietary lock-in, no black-box dependencies, no "you need us to run this." If you want to walk away after the project, you can. The code works without us.
Dedicated PM, not a ticket system
Your PM is a real person who knows your project inside out. They run sprint planning, write handoff documents, flag blockers before they become problems, and join every demo. You talk to them directly — Slack, WhatsApp, email, whatever works.
How long things take.
Discovery call
30 minutes. Problem, data, success criteria.
72-hour prototype
Working demo on staging. Real AI, real data.
Small project ships
Simple AI features, chatbots, single-pipeline tools. $5-8K.
Medium project ships
Multi-component AI products, complex integrations. $15-25K.
Large project ships
Full AI products, multi-pod builds, platform-level work. $30-50K+.
Ready to start?
Book a 30-minute call. We'll tell you if we can prototype it in 72 hours.
Book a Call →