Venkata Manideep Patibandla

I’m an AI engineer. In plain terms, I build AI systems that don’t just look good in a demo — they hold up when real users and real money are on the line. Most of my work comes down to one idea: making AI reliable enough to actually trust in production.

A few things I’ve built:

RelayOps — a customer-support agent for a telecom company that can actually do things (look up an account, check a plan) instead of just chatting. The hard part isn’t the conversation — it’s the guardrails: I built it so it can’t invent fake offers, leak someone’s personal information, or take an unsafe action, then stress-tested it with tricky, adversarial cases to prove it stays in line. Try the live demo.

CostGuard — think of it as a smart switchboard that sits between an app and the AI models it relies on. It quietly checks each AI response for quality, automatically retries or switches to a different model when one falls short, and tracks exactly what every call costs. In testing it cut AI spending by 10–20× versus the obvious default — same quality, a fraction of the bill.

RealDataAgentBench — to make CostGuard’s model-switching smart, I first had to answer a simple but expensive question: which AI model should you actually use, and what will it cost? So I ran 1,412+ head-to-head tests across 12 of the leading AI models on real data tasks. The headline finding: a small, cheap model held its own against the top-ranked one while costing 65× less per task — exactly the kind of result that saves a company real money.

Tether (in development) — a safety net for AI agents that run long tasks, so that if one crashes or a provider goes down halfway through, it can pick up where it left off instead of starting over.

These days I’m an AI/ML Engineer (Contract) at a stealth AI startup, leading a model that estimates what a home is worth from just its address — accurately enough (within about 5%) that lenders can skip a manual appraisal on standard properties, and roughly half as far off as the data provider’s own tool. Alongside that, as a Forward Deployed AI Engineer at SBL, I work hands-on with companies (Emoha, Topmate, Clinik) to automate their sales and operations workflows from start to finish. Earlier, at AnternData Solutions, I delivered AI projects for global tech companies including TigerData (formerly Timescale). I’m also IBM Certified in Agentic AI.