The thesis
The operating model behind every venture we build.
AI Foundry Ventures is not a holding company that owns ventures. It’s a way of building them — fast, regulator-grade, AI-native, in regulated and high-trust markets where most teams take quarters to do what we do in weeks.
01
Production sprints, not prototypes.
Every venture AIFV builds ships in 2–4 week sprints to a working production environment. We don't deliver Figma files and slide decks; we deliver running code, deployed, observable, and handover-ready. The sprint cadence forces decisions early, exposes integration risks before they compound, and means a venture has paying customers — or a measurable reason it doesn't — within a quarter, not a year.
Proof
CortexData shipped its 5-module lending OS, 8 loan products, and full RBI compliance map in successive sprints. FlikVault went from blank repo to live academies on two continents the same way. Hundi’s settlement engine, compliance pipeline, and three-jurisdiction entity structure were assembled module-by-module with the same cadence.
02
Regulators in the room from day one.
Compliance is the substrate, not the wrapper. RBI Master Directions for CortexData. ADGM/FSRA Innovation Test Licence and RBI observer-node access for Hundi. Federation reporting standards (ECB, BCCI, ICC) for FlikVault. We design the data model around the audit trail the regulator will eventually ask for, not the other way around — which is why we ship every regulatory return built-in instead of as an integration project.
Proof
CortexData ships 9+ RBI returns out of the box: KFS, IRACP, PSL Form A, DSB, OSS-3, Co-Lending, Securitisation, Gold Loan, and audit-immutable retention. Hundi embeds FATF Travel Rule with IVMS101 at the protocol level. FlikVault produces federation-grade attendance and progress audits.
03
AI in the core, not bolted on.
Pose estimation in SKrutin. ML decisioning with full feature attribution in CortexData. Claude-written coaching notes in SKrutin. Travel-Rule-with-ZK compliance proofs in Hundi. The AI isn't a feature page on the marketing site; it's how the product fundamentally works. Which means every venture is built on infrastructure that benefits from each new generation of frontier models, not stranded by them.
Proof
CortexData’s 5-model fraud ensemble + calibrated PD scorecard returns per-decision feature attribution. SKrutin runs RIFE interpolation, YOLO/RF-DETR ball tracking, and pose-based biomechanics scoring on iPad. Claude turns every technical analysis into an age-appropriate coaching note.
04
Two markets, deeply.
We operate in two markets — regulated finance and cricket — because depth compounds. The Indian lending stack and the Gulf–India settlement stack share a regulatory grammar, an audit posture, and a customer language. Cricket academies and AI video coaching share a codebase, a vision pipeline, and a federation context. We’d rather be unforgettable in two markets than forgettable in ten.
Proof
AIFV maintains active engagement with KSCA (technology advisor), Cricket Victoria (Melbourne partner), and Delhi Capitals on the cricket side; with co-operative banks, NBFCs, and exchange-house counterparties in the Gulf-India corridor on the fintech side. Reference clients seed each cluster.
How we work
The mechanics, in plain language.
- Sprint length
- 2–4 weeks
- Each sprint ends with a deployed environment a paying customer can use, not a slide deck.
- Team shape
- Senior, full-stack
- Most engineers ship across the stack. We don’t hand off between front-end, back-end, and ML teams; one team owns the venture end-to-end.
- Engagement model
- Sprint or equity
- Three new engagements a quarter. Some are paid sprints with enterprise clients; some are joint ventures where AIFV holds equity.
- Default deployment
- Vercel · AWS Mumbai · on-prem
- Cloud-native by default; on-prem when the customer’s regulator demands it. Same Kubernetes manifests either way.