Everything you need to secure AI agents.
Endpoint-level interception, divergence detection, real-time risk scoring, policy enforcement, compliance evaluation, fleet management, and a tamper-proof audit trail — all from a single daemon.
GET STARTEDNine AI security companies acquired for over $2B in the last 12 months — Protect AI, Lakera, CalypsoAI, Robust Intelligence, SGNL, Koi Security, Prompt Security, Invariant Labs, Astrix. Quint ships with the one capability none of them had: divergence detection.
Why endpoint interception matters
MCP gateways only see user-configured tools. In our analysis of Claude Code, 94% of actions were native tool_use calls — not MCP. Quint intercepts every tool call across 7 LLM API parsers and 21+ agent platforms.
See what your AI agents actually do.
Only 21% of enterprises have full visibility into AI agent activity. Quint intercepts every tool call at the OS level — file reads, API calls, bash commands — visible on your dashboard in real time. Two independent capture layers surface divergence no other tool can detect.
Two independent layers — the TLS proxy captures what agents claim (intent), EndpointSecurity captures what actually happens at the OS level (truth). When an agent says 'read config.yaml' but the OS sees it accessing ~/.ssh/id_rsa, that divergence is the highest-confidence threat signal in the industry.
- Intent layer: proxy intercepts LLM API traffic
- Truth layer: OS-level file, process, and network events
- The gap between them is the signal no one else has
Know every agent on your network.
Multi-layer detection engine identifies all major AI agent platforms automatically. No agent configuration required. Map every agent-to-tool, agent-to-data, and agent-to-agent relationship into a queryable graph.
Six independent detection signals — code signing, process inspection, HTTP headers, system prompt fingerprinting, user-agent patterns, and protocol analysis — achieve reliable identification across 21+ AI platforms.
- Works without agent cooperation
- Detects shadow AI tools
- Retroactive backfill reclassifies early unknowns
Map every agent relationship.
Visualize orchestrator-to-worker hierarchies, track derived agents, and monitor risk propagation across your entire agent fleet.
Every action scored. Every score explained.
A multi-layer scoring engine evaluates every tool call against a proprietary compliance knowledge base covering 16 regulatory frameworks. Deterministic by default, no LLM hallucination risk.
Every action is classified by verb, target sensitivity, and scope. Deterministic scoring with no model dependencies.
- Canonical action taxonomy
- Real-time evaluation
Block, flag, or allow. In real time.
Define what your agents can and cannot do, then enforce it fleet-wide at the edge. No cloud round-trip required. Policies push on heartbeat.
Policy decisions happen locally on the machine in under 10ms. The daemon enforces even if the network is down.
- Real-time edge enforcement
- Works offline
Tamper-proof evidence for every action.
Every tool call is recorded in an Ed25519-signed, SHA-256 hash chain. Cryptographically verifiable, exportable as proof bundles, designed for regulatory auditors.
Each entry includes the hash of the previous entry. Any modification, insertion, or deletion breaks the chain and is immediately detectable.
- Ed25519 + SHA-256 hash chain
- Run quint verify --all to validate
Every machine. One dashboard. Your stack.
Manage daemons, policies, and agent activity across your entire fleet from a single control plane. OCSF-formatted event schema with webhook delivery to Slack, PagerDuty, and your SIEM. Query everything via REST API.
Machine inventory, health monitoring, agent census, and policy distribution from a single dashboard. Heartbeat monitoring catches offline machines.
- One-command deployment via MDM, Ansible, or curl
- Policies push on heartbeat
Secure your agents.
Ship with confidence.
One install. Every agent. Deploy in under 2 minutes. Free for your first two machines.