| What it does | AI penetration testing that proves every vulnerability with independent verification
| Catch your AI agents' mistakes, block the dangerous ones
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| Stage | Not given
| Startup
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| Founded | Not given
| 2026
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| Based in | Not given
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| Pricing model | Paid
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| Pricing | One-off Deep test: €3,500 one-time (includes fix retest). Standard: €990/month (4 scans per month). Deep: €2,900/month. Stress add-on: €900/month. Annual billing includes two months free.
| Free: $0/month with 5,000 conversations/month, Langfuse or LangSmith integration, problems and Slack alerts, rules that block costly actions, no credit card required. Starter: $49/month for 25,000 conversations/month plus email support. Growth: $149/month for 100,000 conversations/month plus priorit
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| Key features | - Identity replay matrix for testing authorization across multiple roles and tenants
- Business logic invariant testing for coupon reuse and price tampering
- Prompt injection and AI agent security testing including MCP servers
- Independent verification with 3x reproduction requirement from clean sessions
- 35 vulnerability classes tested deterministically
- Scope and rules of engagement enforced in code before requests execute
- Trust page for sharing security posture with customers and auditors
- Mapping of findings to security compliance frameworks
- Authorized stress testing with rate-limit discovery and circuit-breaker controls
| - Monitor AI agent conversations without code by connecting Langfuse or LangSmith
- Judge conversations on six criteria: accuracy, goal alignment, decision quality, completeness, helpfulness, and factuality
- Create code-based rules that block risky actions before they run
- Group failures into problems with suggested rules and failure counts
- Send Slack alerts for serious mistakes and reply checks immediately
- Add to agents with one line of Python code for OpenAI Agents SDK, LangChain and LangGraph
- Mask sensitive data like email addresses, phone numbers and card numbers before sending to Kalytera
- Rules continue running offline if Kalytera goes down
- Correct judge verdicts by marking conversations as passed or failed
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| What makes it different | - Reports only verified findings that are reproduced independently from clean sessions
- Detects cross-tenant authorization flaws through identity replay that scanners miss
- Identifies business logic flaws that signature-based scanners cannot catch
- No-finding-no-fee guarantee on first deep test
- Tests AI agents and prompt injection with canary verification
| - Rules are code-based, not AI, so they cannot be overridden or argued with
- No code setup using Langfuse or LangSmith connections for immediate visibility
- Rules continue protecting agents even when Kalytera is offline
- Catches exact mistakes from real AI agent incidents like database deletes, account takeovers and crypto theft
- Customer data stays on your servers; Kalytera only reads conversations, never writes or stores sensitive data
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 1 ● no change since last check |
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| Trust Flow (Majestic) | 2 | 0 |
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| Citation Flow (Majestic) | 1 | 14 |
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| Referring domains (Majestic) | 2 | 28 |
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SuperPentest