Rajamohan Jabbala
AI/ML innovation leader and founder of CLS++. Twenty years turning hard research problems into products people trust.
Founder, AlphaForge AI Labs · Ex-Amazon Alexa · Two-time CTO
“An agent that can't trust its own memory can't be trusted with anything that matters. I'm building the reliability layer that earns that trust.”
Why I'm building CLS++
Agent memory layers kept silently dropping facts and blindly overwriting them — and you'd only find out in production. CLS++ is a memory engine that doesn't: it archives every superseded fact with full lineage, survives embedder failures, and lets you prove what changed. Memory you can actually trust.
The pedigree
Chief Technology Officer
Bonito Designs- Built Project Raven — cut design retrieval from 1 day to 500ms
- Shipped AI sales agent “Suchi”, automating 400+ calls a day
- Stood up MLOps that lifted scalability 40%
Chief Technology Officer
Convergent Inc- Led a $200M enterprise cloud transformation
- Built real-time ML analytics pipelines
- 92% reduction in reconciliation time
Software Development Manager
Amazon — Alexa- Launched the Alexa × Prime Video platform (3.5% conversion)
- Created “Clairvoyant” — capacity planning from 1 week to 1 minute
M.Tech, Computer Engineering
IIT Madras · 1997–2000
M.S, Applied Statistics
Osmania University · 1995–1997
Patents & invention
Cutlist Optimization Ensemble Algorithm
Govt. of India
Thermodynamic memory architecture (CLS++)
Provisional
Elastic Neighbourhood
Govt. of India
Raster Snap function for Vectorization
IEEE
Selected work
CLS++
Memory engine
Reliable memory for AI agents — archives every superseded fact with full lineage, survives embedder failures, and lets you prove what changed.
Agent Transport Protocol
Rust · protocol
The TCP/IP of AI agents — a five-layer stack for trust-aware, economically-optimal multi-agent networking. ~37k lines of production Rust.
deepAudit
AI SaaS
AI-powered software deep audit — 750+ signals across 40 categories. One API call to audit any GitHub repository.
Quant Trading Engine
Python · fintech
A quant-based trading engine and service built to put institutional-grade strategy automation in the hands of retail traders.
Off the clock: finished the 300km Paris-Brest-Paris randonnée in under 15 hours. The same appetite for long, hard problems shows up in the code.
Build on memory you can trust
Give your agents a memory layer that never silently loses or wrongly overwrites a fact.