Straiker is an agentic AI security platform. It gives teams visibility and control over every AI agent in their environment, from first build to live deployment.
It sits in the AI security tools category, but focuses on agents, MCP servers, and multi-tool workflows rather than general model safety.
The California company was founded in 2025 and raised a $64 million Series A in June 2026, bringing total funding to about $85 million.
Investors include Marathon Management Partners, Citi Ventures, Illuminate Financial, and Workday Ventures, with earlier backing from Bain Capital Ventures and Lightspeed.
The Ascend AI results view breaks a test run down by risk category and plots every attack attempt on a threat matrix.
What is Straiker?
Straiker splits AI-agent security into three modules that map to the agent lifecycle: Discover AI (inventory and posture), Ascend AI (pre-deployment adversarial testing), and Defend AI (runtime protection).
The three feed each other. Production detections sharpen the testing engine, and flaws found in testing strengthen runtime blocking.
Key Features
| Module | What it covers |
|---|---|
| Discover AI | Inventory of agents, MCP servers, and agentic workflows; posture monitoring; misconfiguration detection |
| Ascend AI | Pre-deployment adversarial testing for prompt injection, goal hijacking, tool misuse, inter-agent manipulation |
| Defend AI | Runtime blocking of prompt injection, data exfiltration, agent manipulation, and malicious or vulnerable MCP connections |
| Threat data | Testing and runtime share a feedback loop; STAR Labs research feeds new attack techniques |
| Target agents | Internally-built and third-party agents, coding agents, productivity agents, multi-tool AI apps |
Adversarial testing before deployment
Ascend AI is the pre-production step. Driven by Straiker’s proprietary threat data, it surfaces vulnerabilities in an agent’s tools, MCP connections, and workflows before it goes live.
The attack classes are agent-specific. Prompt injection and goal hijacking bend an agent’s intent; tool misuse and inter-agent manipulation abuse the systems an agent can reach.
Each assessment produces an executive summary and grades the agent against categories like data leakage and LLM evasion.
Runtime protection
Defend AI is the live layer. It watches agents in production and blocks prompt injection, data exfiltration, agent manipulation, and malicious or vulnerable MCP connections as they happen.
Straiker states the runtime controls run without degrading agent performance. Detections at this layer also feed back into Ascend AI, so the testing engine keeps learning from real attacks.
Defend AI lists discovered applications and MCP servers next to runtime controls you toggle between Detect and Protect per threat type.
When to Use Straiker
Straiker fits enterprises that are deploying AI agents, MCP servers, and multi-tool workflows and need to inventory, test, and defend them as a group.
The vendor describes its user base as Fortune 500 enterprises and frontier AI labs. Named customers include Omada Health, Coupa, American Express Global Business Travel, Enterprise DB, and Automation Anywhere.
For teams focused on protecting a single LLM application rather than a fleet of agents, a runtime guardrail like Lakera Guard covers narrower ground. Straiker’s scope is the agent estate end to end.