Our Story
Where DevSecOps and FinOps converge for AI
We started CerebrixOS after watching the same pattern repeat across every team adopting AI: two functions that should have been working together — DevSecOps and FinOps — were operating in completely different rooms. Security and governance teams were trying to write policy for systems they couldn't see into. Finance and platform teams were watching token spend balloon with no way to attribute, cap, or control it. Engineering was caught in the middle, shipping fast against constraints nobody had agreed on yet.
The deeper we looked, the clearer it got. Every model vendor had its own SDK, its own auth, its own usage dashboard, its own idea of what a "guardrail" meant. Costs ballooned because there was no shared layer to route requests, set ceilings, or fall back across providers. Governance lagged because there was no single place to apply policy, log decisions, and prove what happened. Two operational disciplines that the rest of the stack had already merged — security and cost — were drifting apart again, just for AI.
We became convinced that AI needed a control plane where DevSecOps and FinOps converge: one place where policy, auditability, and token economics are designed in from the first request, not bolted on after the bill arrives or the incident review starts.
That's what Tuning Engines is. One OpenAI-compatible API in front of open models, frontier commercial models, and your own tuned models — with centralized policy control, full request-level auditability, and cost ceilings, quotas, and routing applied to every call. Teams keep their existing SDKs. Security gets traceability. Finance gets predictable spend. Engineering stops being the referee.
Today, we're backed by programs like Google Cloud for Startups, NVIDIA Inception, and AWS Activate. But at our core, we're still a small team with one conviction: secure, govern, and optimize every AI interaction — and treat that as a single job, not three.
That's the future we're building — and we'd love for you to be part of it.
Meet the Team
The people behind Tuning Engines
Venkat Chandra
Founder & CEO
After years leading consulting engagements across industries, VC saw the same pattern everywhere — organizations pouring millions into AI pilots that never made it to production. The gap between "impressive demo" and "real-world impact" was massive. He founded CerebrixOS to close that gap, and Tuning Engines is the core of that mission: giving teams sovereign, production-ready models without the infrastructure nightmare.
Shainu Suhas
Chief Technology Officer
Shainu lives at the intersection of generative AI, computer vision, and NLP — driven by a deep curiosity for how intelligent systems can learn and create. He leads the technical architecture behind Tuning Engines, from model training pipelines to evaluation frameworks, constantly pushing the boundaries of what domain-specific fine-tuning can achieve.