Product-Led AI Engineering Studio
Zero to Market.
In 12-20 weeks.
An end to end product-led engineering studio for zero-to-one AI products including architecture, design, data analytics, seo, accessibility, evals, legal, compliance, and everything needed to reach product market fit.
“We are a product-led engineering lab, not a consulting agency.”
Most consulting contracts end on a date. Ours end on a milestone: Product Market Fit.
01 / Lifecycle
What idea to product market fit looks like.
Foundation
Architecture from the Discovery Sprint. Set Precision eval targets across functional, qualitative, and safety dimensions. CI runs evals on every commit.
Build to alpha
Weekly Friday demos. Failing evals block deploys. Compliance finalised: HIPAA, DPDP consent, audit logging. Alpha to 10 trusted users.
Production-harden
Latency, cost, observability, error budgets. Postmortem culture begins — every incident becomes a regression test in the eval suite.
PMF hunt
Real users at scale. Rapid iteration. We rebuild components if the data demands it. Engagement converts to an Embedded Pod or hands over cleanly.
02 / Crew
Who's on the team?
Squad of 4-5 in each pod.
Senior, embedded
Forward Deployed Product Engineer
Owns the engagement. In your Slack. On your weekly.
AI + full-stack
2× Senior Engineers
Write the production code, run the evals, own the deployments.
UX for AI
Product Designer
Trust, explainability, consent flows, dashboards.
As needed
Compliance Lead
HIPAA / DPDP architecture, BAA flow, audit posture.
03 / Cadence
Progress-based milestones. Every Friday.
Not a status update. Progress-based milestones. A working demo, a 3-line summary of what changed and didn't, and most importantly why.
- Working demo of what shipped this week
- Metrics that matters for your business
- Three-line change log — what moved, what didn't, and why
- Plan of action for next week's scope
Acquisition rate
97%
User engagement
96%
Retention rate
72%
Average revenue per user
$100/month
Ship summary · Week 6
We implemented HIPAA-compliant audit logging for all inference calls. We refactored context retrieval to reduce noise on long-form prompts. We implemented a new feature that will allow users to export their data in a CSV format.
Next week's goal
Next week's goal will be to improve retention rate which has dropped by 4% since last week.
04 / Work
Shipped, evaluated, in production.
Healthcare · Women's SRH · India · NGO
M-Health
Built a trusted path to women's SRH care—because distance, language, and shame should never decide who gets help.
39,334
Downloads
101,121
Minutes of video watched
Healthcare · Women's Health · TCM
Qi Health
Built a telehealth platform for personalised Traditional Chinese Medicine — custom herbs, virtual consults, and care plans for women's health.
Consumer · AI
SatvikScan
Shipped an in-aisle label scanner that turns ingredient doubt into a clear dietary verdict in seconds.
Healthcare · Women's SRH · WhatsApp · NGO
Myna Bolo
Shipped Myna Saheli: A multilingual WhatsApp AI health companion breaking barriers to sexual and reproductive health access.
100,000+
Total Conversations
23,700+
Unique Engaged Users
Healthcare · Voice AI · Women's SRH · India
Myna Voice AI
Engineered Myna Voice: A low-latency conversational voice AI enabling phone-based SRH care for low-literacy rural women.
5,269
Total Calls Completed
588
Unique Callers
05 / Lab
What we cook in-house.
Every 0→1 starts with a Discovery Sprint.
Two weeks. We meet your team, your data, your constraints. You get an architecture and an honest call on whether to proceed. Most do.
Apply for a sprint →