About us

We built the governance layer
AI agents were missing.

Agent frameworks were built to give AI autonomy. Cortega was built to give enterprises control. We bring carrier-grade policy enforcement, zero-trust tool access, and real-time auditability to agentic AI.

The problem

Every major agent framework handles what agents can do. None handle what they're allowed to do.

LangGraph, CrewAI, the OpenAI Agents SDK — they give agents capabilities. They don't answer the questions a CISO asks: Which systems can this agent access? What happens when it sends patient data to an LLM provider? Who approved that transaction? Where's the audit trail?

Organizations trying to deploy agents in regulated environments — healthcare, finance, legal, and enterprise technology — kept running into the same wall. The agent worked. The organization could not approve it. Security teams had no visibility. Compliance teams had no evidence. Legal teams had no audit trail. The gap was governance.

Why we're built this way

We built the first Session Border Controller. This is the same problem, for AI.

At NexTone, we built the first Session Border Controller (SBC), the network element that secures VoIP at the boundary between carriers and enterprises. VoIP had the same trust problem AI agents have now: you can't secure a call by trusting the endpoint to behave. Enterprises learned to enforce identity, policy, and audit at the network perimeter instead, with SBCs and policy gateways sitting between every call and the network it touched, rather than trusting the phone or the softphone client to police itself.

Agentic AI has the same shape. An agent's own prompt and instructions are the endpoint, and endpoints can be manipulated, jailbroken, or simply wrong. Cortega is the SBC for AI: an external, deterministic governance gateway that enforces policy on every request in the path, rather than asking the agent to self-police through prompt instructions alone.

That's the discipline we're building to. Our team ran carrier-grade infrastructure handling billions of mission-critical transactions, where five-nines reliability, identity validation on every call, and tamper-proof audit trails weren't aspirational, they were the baseline. Cortega holds AI governance to the same bar.

Leadership

Who we are.

Operators who've built and scaled before.

Sri Ramachandran

Sri Ramachandran

Co-Founder & CEO

5x CXO/GM. Enterprise technology executive with 25+ years leading product, technology, and business strategy across high-growth and publicly traded companies. Leads Cortega's vision to bring carrier-grade operational rigor and governance to enterprise agentic AI.

LinkedIn ↗
Medhavi Bhatia

Medhavi Bhatia

Co-Founder & CTO

Pioneering systems architect and engineering executive across telecom and healthcare. Co-architect of the original NexTone Session Border Controller, with deep expertise in mission-critical distributed systems, boundary security, and zero-trust data protection.

LinkedIn ↗
Track record

Operating experience most AI governance vendors don't have.

25+
Years of collaborative engineering and leadership
Billions
Mission-critical transactions handled across telecom and healthcare infrastructure
3
Successful exits
5×
Combined CXO leadership, taking high-growth enterprise infrastructure to market
What we believe

Four principles that shape how we build.

01

Governance belongs at the gateway, not inside the agent

Putting security and compliance logic inside the agent means every agent has to be secured individually — and an agent that's been manipulated can bypass its own controls. Enforcement at the gateway means no agent can route around it, the same reason VoIP moved trust from the endpoint to the Session Border Controller.

Outcome: one enforcement point in front of every agent and model, not custom guardrail code duplicated — and drifting — across every team.
02

Private by default: Governance must live where your data lives

For regulated teams, where data is processed matters. Cortega is built so governance can run close to the AI traffic, in the environment the organization controls.

Outcome: sensitive data never leaves your network to get governed, including fully disconnected, air-gapped deployments.
03

Compliance evidence should accumulate as agents operate

Assembling evidence at review time means relying on logs that may not have been designed for that purpose. Cortega records structured evidence at the moment policy is applied.

Outcome: an audit trail that's already built when a reviewer asks for it, not a scramble to reconstruct one from scattered logs.
04

Governance should enable adoption, not slow it down

The organizations that scale AI programs are the ones that solve governance first. A security team that can see what agents are doing, enforce policy, and produce evidence will say yes faster than one that can't see anything at all.

Outcome: security and compliance teams that clear new AI use cases faster, because they can see and control what's happening.
Standards

Built to the frameworks regulated buyers actually ask for.

Cortega's architecture is built around the control expectations of the frameworks regulated buyers are already accountable to, not retrofitted after the fact.

This isn't just a regulated-industry problem. Every organization running agents has systems it can't let an agent misuse, spend it can't let run away, and shadow AI usage it can't see, whether or not an auditor is asking. The frameworks below are the sharpest version of a need every enterprise has: know what your agents are doing, and be able to prove it. See how this plays out for teams outside regulated industries.

Enforced today

  • GDPR and HIPAA readiness, from the Enterprise tier up.
  • Human oversight on high-stakes actions, in line with EU AI Act Article 14.
  • Deterministic PII/PCI detection, not a probabilistic best guess.
  • Continuous audit evidence instead of point-in-time log exports.

Roadmap aligned

  • SOC 2 observation period, with CI, access-review, and change-management evidence.
  • Governance controls aligned to NIST AI RMF and ISO/IEC 42001.
  • CMMC 2.0 and FedRAMP Moderate third-party assessment.

Want to learn more or work with us?

Wherever you're coming from, there's a direct path to the right conversation.

Schedule a 1-on-1 AI Architecture and Policy Review → Explore Telemetry & Benchmarks → Contact the Founders →