| What it does | Independent AI verification and production control layer
| 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 | Freemium
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| Pricing | Starter: $166/month ($1,990 billed annually) with 12,000 test runs/month, 3 applications, and validated fixes at $25 each. Team: $833/month ($9,990 billed annually) with 55,000 test runs/month and 10 applications. Business: $2,083/month ($25,000 billed annually) with 165,000 test runs/month, 25 appl
| 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 | - System Graph mapping of services, dependencies, ownership, and policies
- Verification Engine with 19 verification domains from unit tests to compliance
- Continuous verification and change detection
- Policy-based control and approval workflows
- Durable evidence and audit trails
- AI-assisted remediation with outcome-based billing
- Integration with CI/CD, cloud, and observability tools
- VPC, private cloud, on-prem, and air-gapped deployment
- Identity-first with RBAC and SSO
- Secure Enclave Runner for restricted environments
| - 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 | - Independent verification separates proposing changes from deciding if available evidence is sufficient
- Model-independent design works with any approved model or deterministic systems alone
- Outcome-based billing charges only for validated fixes that pass verification
- Governance by default with explicit approval, audit, and no shared credentials
- Topology-aware impact analysis using System Graph to recommend validation plans
| - 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) | 28 ● no change since last check | 1 ● no change since last check |
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| Trust Flow (Majestic) | 5 | 0 |
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| Citation Flow (Majestic) | 20 | 14 |
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| Referring domains (Majestic) | 62 | 28 |
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