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Understanding Operant AI

Operant AI is a runtime security company that protects AI applications, AI agents, MCP servers and the APIs and Kubernetes workloads beneath them. Its customers are enterprises that are putting agents into production and need to see, and control, what those agents and tools actually do.

The platform watches live traffic and behaviour rather than reviewing configurations after the fact. It runs from cloud workloads to employee laptops, where coding agents and unsanctioned AI tools increasingly operate, and it treats agents and MCP connections as non-human identities that need their own access controls.

At A Glance

VendorOperant AI, Inc.
CategoryRuntime security for AI agents, MCP, APIs and cloud workloads
Identities coveredAI agents and agentic non-human identities, MCP clients and servers, APIs, employee devices
DeploymentKubernetes-native and hybrid cloud, private SaaS, VPC, on-premises and air-gapped; endpoint app for macOS, Windows and Linux
Agentic AIAgent Protector, MCP Gateway, Semantic Firewall, Endpoint Protector
CertificationsSOC 2 Type II
FundingSeries A led by SineWave Ventures and Felicis (2024)
Market classificationAgentic AI Identity; also Workload Identity

What Operant AI Does

Agents call tools, tools call APIs, and a weakness anywhere in that chain can expose data. Operant’s approach is to secure the whole chain at runtime rather than one link of it, starting with the APIs and Kubernetes workloads underneath and working up through AI applications, MCP traffic and the agents themselves to the employee workstation. Each layer is enforced where the traffic actually flows, and policy decisions increasingly turn on what an action is trying to achieve rather than on fixed rules about endpoints.

Products

API & Cloud Protector

API & Cloud Protector is for teams whose APIs run on Kubernetes-native stacks and need threat protection beyond a web application firewall. It covers both north-south traffic entering the cluster and east-west traffic between services.

AI Gatekeeper

AI Gatekeeper defends AI applications and agents at runtime. It detects threats against agents, assigns them trust scores and blocks unauthorised ones, applies OWASP-aligned threat modelling and extends identity and access controls to MCP and AI non-human identities. It works without the cost or overhead of VPC traffic mirroring.

MCP Gateway

MCP Gateway, part of AI Gatekeeper, gives security teams control over the MCP tools their agents use. It builds live catalogues of MCP tools and agents across environments, applies least-privilege execution and granular permissions to tool usage, and sets trust zones that block untrusted servers and tools, with rate limiting and encryption enforcement. A central governance framework covers agent and tool management across the enterprise.

Agent Protector

Agent Protector addresses the agents that appear across cloud and SaaS faster than security teams can track them. It discovers unmanaged agents, MCP servers, tools and their dependencies, builds agentic identity catalogues and enforces zero trust controls designed for agentic AI.

Endpoint Protector

Endpoint Protector covers the AI tools employees run on their own machines. It inventories sanctioned and unsanctioned AI tools, MCP servers and plugins, watches for prompt injection, identity anomalies and exfiltration of personal data, and redacts secrets and keys automatically.

Semantic Firewall

Semantic Firewall enforces policy on intent. It works out the purpose behind every prompt, tool call, command and data movement in real time and returns allow, block or redact decisions. Four guards split the work:

Tool Intent GuardBlocks exfiltration, bulk dumps, credential access and unauthorised sharing
Code Intent GuardStops malicious execution, injection, shell breakout and privilege escalation by coding agents
Data Intent GuardApplies Microsoft Purview sensitivity labels
Scope GuardKeeps agents within scope, with natural-language policies such as “no unauthorized deletes”

Woodpecker

Woodpecker is an open-source automated red teaming engine. It tests Kubernetes misconfigurations, API security and AI models for prompt injection and data poisoning.

How It Works

The cloud products are Kubernetes-native and run from Kubernetes to hybrid and private clouds, including remote agents on Google Vertex AI.

ComponentWhat it does
Endpoint layerEndpoint Protector is a native workstation application, rolled out across fleets through standard MDM and JAMF workflows and tied to the enterprise identity provider.
Data handlingIn private mode, sensitive prompts, agent traces and detected data stay inside the customer’s environment, and private SaaS options support data residency.
Decision pointSemantic Firewall classifies intent with Operant’s own models, and every decision is made inside the enterprise environment, including VPC, on-premises and air-gapped deployments.

Identities And Systems Covered

AI agentsManaged and unmanaged agents.
Agentic non-human identitiesAgent and MCP identities, with identity and access controls.
MCPServers, clients, tools and connections.
SecretsSecrets and keys on employee endpoints.
Cloud platformsKubernetes, Amazon EKS, Fargate, Bedrock, Azure and Google Cloud.
Data and SaaS platformsDatabricks, Snowflake and Salesforce.
LLM providersOpenAI, Deepseek, Cohere, Anthropic and Hugging Face.

Company Background

Founders and leadershipVrajesh Bhavsar (co-founder and CEO), Dr. Priyanka Tembey (co-founder and CTO) and Ashley Roof (co-founder and CMO).
HeadquartersSan Francisco, United States.
Funding$10M Series A in 2024.
RecognitionFeatured by Gartner across five AI security categories, including the AI TRiSM Market Guide and the API Protection Market Guide.

Note: This overview is compiled from Operant AI’s publicly available information as of 3 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.

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