Rein Security makes a runtime security platform for enterprise AI agents. It gives security teams a view of what homegrown agents, MCP servers and AI apps actually do in production, and blocks a malicious action without stopping the agent that attempted it.
It is aimed at enterprises that build their own agents and need the same control over them that they expect for any production service, with agent data kept on their own infrastructure. The short version of the idea: “Stop the attack. Not the agent.”
At A Glance
| Vendor | Rein Security |
|---|---|
| Category | Runtime security for enterprise AI agents |
| Identities covered | AI agents, MCP servers, applications and the users who trigger agent actions |
| Deployment | Sidecar next to agents, on the customer’s own servers |
| Agentic AI | Agent discovery, behavioural baselines and action-level controls |
| Customers | Dun & Bradstreet, Lemonade, Flex, Swimlane, H&R Block |
| Founded | 2024 |
| Market classification | Agentic AI Identity |
What Rein Does
Enterprises are deploying agents that query databases, call APIs and touch files on behalf of users, often faster than security teams can track them. Rein addresses that gap with a layer that captures everything an agent or application does at execution time. Enforcement is aimed at the single harmful action rather than the whole agent, so the agent keeps working while the attack is stopped, and every action is linked back to the person whose request started it. The platform reportedly secures thousands of AI agents executing millions of actions.
Products
Visibility
Visibility answers the question security teams struggle with most: what did this agent just do, for whom and why. It captures “every database access, every API call, every prompt and response”, traces the actual queries, calls and file access behind each agent action, and keeps an audit log that ties every access to the user who triggered it. Network connections and binary executions are recorded as well.
Guardrails
Guardrails protect running agents against prompt injection, hallucinations and misconfigured tools without downtime. Rein learns each agent’s normal behaviour and blocks only deviations from it. Turning on Protect Mode enforces that baseline automatically, and action-level controls micro-segment the resources an agent is allowed to reach.
Posture
Posture helps teams find and fix weaknesses across agents, models, tools and dependencies as they occur, with each finding mapped to MITRE ATT&CK and ATLAS and carrying context across the user, agent and data path. Its vulnerability management concentrates on the code and CVEs that are actually executing, so effort goes where the risk is real. Findings and audit records, including the data and reasoning behind an agent’s decisions, support compliance work for ISO 42001, the EU AI Act, NIST AI RMF and SOC 2.
Privacy
Privacy is for organisations that cannot send agent data to an outside security service. Rein keeps data in house by running on the customer’s servers with no gateway or proxy in the path, which preserves data sovereignty.
How It Works
Rein deploys once, as a lightweight patented sidecar next to the agents, and from there discovers agents, MCP servers and services across CI, cloud and toolsets.
| Component | What it does |
|---|---|
| Sidecar | Observes the AI-native runtime, the actual execution layer of the agent, and analyses prompts, API calls and database access in place. |
| Behavioural baseline | Builds a dynamic model of each agent’s normal behaviour, which Protect Mode then enforces. |
| Inventory | Maps agents, MCP servers, applications, libraries and APIs as they run. |
Data stays on the customer’s infrastructure throughout, because analysis happens in the sidecar rather than in an external service.
Identities And Systems Covered
| AI agents | Homegrown enterprise agents and AI apps, found automatically at runtime, including those built with frameworks such as Claude, LangChain and Microsoft Foundry |
|---|---|
| MCP servers and tools | MCP servers, tools and service-to-service interactions, all supported in production |
| Human initiators | The users whose requests set agent actions in motion |
| Identity context | Access decisions that take into account which user, from which group, is executing which action |
| Systems | Databases, APIs, file systems and network connections that agents reach |
Company Background
| Founded | 2024 |
|---|---|
| Headquarters | New York City and Tel Aviv |
| Leadership | Matan Bar-Efrat, co-founder and CEO; Netanel Rubin, co-founder and CTO |
| Funding | Emerged from stealth in January 2026 with $8M, followed by a $25M Series A co-led by Glilot Capital and Sienna Venture Capital with Corner Ventures, for a reported $35M in total |
| Growth | A reported eightfold rise in revenue alongside five times more customers |
| Recognition | Selected for TechCrunch’s 2026 Startup Battlefield 200 |
Note: This overview is compiled from Rein Security’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.