llm-security
(11)
Compliant LLM
Compliant LLM (formerly FiddleCube, YC W23) is an AI security and compliance toolkit that helps infosec, compliance, and GenAI teams keep their AI agents, prompts, and MCP servers secure. It red-teams AI systems against attacks like prompt injection and jailbreaking, checks them against frameworks such as NIST, ISO, OWASP, GDPR, and HIPAA, and monitors employee use of third-party GenAI tools to catch data leaks and PII exposure across both approved and shadow AI workflows.
Silmaril
Silmaril is a San Francisco security startup building a runtime firewall for AI agents and AI-native applications. It intercepts prompt injections, context poisoning, and dangerous tool calls in real time - a self-healing classifier that hunts for new attacks against a customer's own environment and retrains itself continuously. Founded in 2026 by Aum Upadhyay (ex-AWS security) and Eduardo Velasco (whitehat who has found exploits in major AI systems), Silmaril is part of Y Combinator's 2026 batch.
ORION Security
ORION Security is an AI-native data loss prevention (DLP) company that protects enterprises from data leaks without relying on manually written policies. Founded in 2024 by Nitay Milner and Jonathan Kreiner, ORION uses large language models and specialized AI agents to map how data normally flows across SaaS, email, cloud, endpoints, and AI tools, then analyzes content sensitivity, user identity, behavioral intent, and data lineage to catch exfiltration and insider threats in real time. The platform targets the three core sources of data loss - human error, malicious insiders, and external attackers - while cutting the false positives and maintenance burden that plague legacy DLP.
Zenity
Zenity is a cybersecurity company that builds an end-to-end security and governance platform purpose-built for AI agents. Founded in 2021 by Ben Kliger and Michael Bargury, it gives enterprises visibility and control over what AI agents - from Microsoft Copilot and Salesforce Agentforce to home-grown builds on AWS Bedrock - can access, do, and invoke. Zenity covers the full agent lifecycle with discovery, posture management, real-time threat detection, and response across SaaS, cloud, and endpoint environments, closing the blind spots that traditional model-focused security tools miss.
Straiker
Straiker is a Sunnyvale-based agentic AI security company that helps enterprises deploy AI agents without handing attackers the keys. Its platform spans three jobs - Discover AI maps the agents, MCP servers, and workflows running across a company; Ascend AI red-teams them before deployment to surface prompt injection, goal hijacking, and tool misuse; and Defend AI blocks identity abuse, memory poisoning, and data exfiltration at runtime. Founded by former Palo Alto Networks and Akamai security leaders, Straiker raised a $64M Series A in June 2026, bringing total funding to $85M.
Vijil
Vijil is a Menlo Park-based AI company building trust infrastructure for enterprise AI agents. Founded in 2023 by senior AWS leaders, its modular platform tests, defends, and continuously hardens agents so they are verifiably reliable, secure, and safe - cutting the time it takes enterprises to trust an agent from about six months to six weeks. Vijil raised $17 million in 2025 (total $23 million) and was named a Gartner Cool Vendor.
Enkrypt AI
Enkrypt AI is a Boston-based AI security company that builds a control layer between enterprises and the large language models and AI agents they deploy. Founded in 2022 by Yale PhDs Sahil Agarwal and Prashanth Harshangi, its Sentry platform combines automated red teaming, runtime guardrails, and compliance monitoring to detect vulnerabilities like prompt injection, jailbreaks, bias, and data leakage before and after models reach production. The company also publishes a free LLM Safety Leaderboard and widely cited red-team research, including a January 2025 report finding DeepSeek-R1 far more likely than rivals to produce harmful content.
Impart Security
Impart Security is a San Francisco cybersecurity company building a unified runtime protection platform for AI, APIs, and web applications. Founded in 2020 by Signal Sciences veterans Jonathan DiVincenzo, Marc Harrison, and Brian Joe, the company merges WAF, API security, Cloud Application Detection & Response, and AI Runtime Protection into one engine that runs autonomous defense agents inside production traffic.
Dropzone AI
Dropzone AI builds an autonomous AI SOC analyst that investigates 100% of security alerts around the clock, mimicking the reasoning of an expert human analyst across phishing, endpoint, network, cloud, identity, and insider-threat domains. Founded in 2022 by former ExtraHop AI lead Edward Wu, the Seattle company replaces playbook-driven busywork with end-to-end investigations and high-fidelity reports, letting overwhelmed security teams focus on real threats. It has raised $57.35M to date, including a $37M Series B in July 2025.
Dynamo AI
Dynamo AI is a San Francisco-based enterprise AI security and governance company that helps regulated organizations deploy generative and agentic AI safely. Born out of MIT CSAIL research, its platform - spanning DynamoEval, DynamoGuard, and AgentWarden - tests AI systems for vulnerabilities, applies real-time, customizable guardrails against threats like prompt injection, data leakage, and hallucinations, and produces the compliance documentation enterprises need to meet regulations such as the EU AI Act.
WitnessAI
WitnessAI is an enterprise AI security and governance platform that helps organizations safely deploy AI at scale. Built on three pillars - Observe, Protect, and Control - its platform provides real-time visibility into all AI interactions (employee tools, internal models, AI agents, MCP servers), detects and blocks prompt injections and jailbreaks with over 99% accuracy using intent-based ML models, and enforces behavioral policies without code changes. With $85.5M in total funding, 500% ARR growth in 2025, and customers across financial services, telecom, airlines, and automotive, WitnessAI is positioning itself as the confidence layer enterprises need to move from AI experimentation to production deployment.