Security testing, evaluation, compliance, cost tracking, and observability in one platform. No duct tape required.
Describe your AI application in natural language. Our proprietary pipeline analyzes your app profile, maps domain-specific risks, generates targeted test cases, and assembles a production-ready evaluation config — powered by EvalGuard's multi-model orchestration engine.
An AI attacker probes your LLM across multiple conversation turns, adapts its strategy based on resistance, and finds vulnerabilities that static tests miss. Powered by UCB1 bandit optimization.
The industry's most comprehensive red teaming suite. Test your AI systems against prompt injection, jailbreaks, data exfiltration, and 228 more attack vectors across 43 unique strategies.
166 built-in scorers covering faithfulness, relevance, toxicity, hallucination, coherence, and more. Create custom assertions with LLM-as-judge rubrics or deterministic rules.
Connect to OpenAI, Anthropic, Google Gemini, Meta Llama, Mistral, Cohere, and 80 more providers through a single unified interface. Switch models with one line of config.
Track spend per model, per prompt, and per team. Set budget alerts, forecast costs, and identify optimization opportunities before they become invoice surprises.
Map your AI systems to OWASP LLM Top 10, NIST AI RMF, MITRE ATLAS, EU AI Act, ISO 42001, India DPDP, and HIPAA. Generate audit-ready reports, track compliance drift, and maintain documentation automatically.
Visual rule builder for real-time prompt and response filtering. Semantic matching, regex patterns, and PII detection. Published p95: 2.57ms across 20K runs (see /trust/latency).
Version control your prompts like code. View diffs, roll back to any version, require team approvals, and deploy to production with confidence.
Automated compliance assessment across 33 regulatory frameworks. EU AI Act risk classification, gap analysis, remediation plans, and audit-ready documentation — all generated automatically.
Board-level view of your entire AI governance posture. Track compliance scores, active incidents, vendor risks, and cost analytics in a single CISO-ready dashboard.
When AI goes wrong, EvalGuard provides structured incident response with root cause analysis templates for 11 AI failure categories — from hallucinations to compliance violations.
Track third-party AI vendor risks, DPA status, lock-in scores, and policy changes. Pre-built profiles for OpenAI, Anthropic, Google, and Mistral.
Define and enforce SLA targets per model and endpoint. Track availability, latency percentiles, error rates, and throughput with automatic violation alerts.
When model behavior drifts, EvalGuard automatically triggers re-evaluation. Configurable thresholds, cooldowns, and daily limits prevent alert fatigue.
Scan pickle files, PyTorch checkpoints, and ONNX models for backdoors, trojans, and malicious payloads before deploying them to production.
Detect unauthorized AI usage across your organization. Monitor which models employees use, flag PII in outbound prompts, and block unapproved providers — all through your AI gateway.
Discover every AI model in your organization, map data flows, detect misconfigurations, and get a unified posture score. Like Palo Alto Prisma — but for AI.
Paste your scan or eval results — the copilot auto-analyzes findings, prioritizes by risk, suggests step-by-step fixes with code examples, and maps compliance impact.
Route all LLM traffic through EvalGuard's gateway for automatic security scanning, cost tracking, rate limiting, and observability. One line base URL change.
Full distributed tracing for AI agents. Visualize multi-step agent trajectories, track token usage per step, analyze RAG pipeline quality, and detect hallucinations.
Scan pickle, safetensors, GGUF, and ONNX model files for malicious opcodes, tampered tensors, and smuggled payloads before loading them into production. Pure-TS implementation — never executes attacker code.
Agentless discovery of every AI resource in your cloud — foundation models, custom models, endpoints, Bedrock agents. Risk-scored with deprecated-model flags and network-exposure factors.
Audit every tool call flowing through MCP. Detect unauthorized tool use, memory poisoning, and policy violations in real time. Risk-scored log of agent behaviour.
Published, reproducible latency numbers for the full firewall pipeline (pattern + token + semantic + output layers) — measured, not claimed.
Start free with 10,000 evaluations per month, or get a personalized demo from our team.