| What it does | Catch your AI agents' mistakes, block the dangerous ones
| Feature flags, A/B tests, guardrails and LLM experiments for web and React Native
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| Stage | Startup
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| Founded | 2026
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| Based in | Not given
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| Pricing model | Not given
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| Pricing | 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 | - 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
| - Feature flags and rollouts
- A/B testing and experiments
- AI configs for LLM experiments
- Guardrails to protect metrics
- Goals and metrics tracking
- Audience targeting
- Results and statistics analysis
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| What makes it different | - 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
| - In-process decisions add no latency to requests
- One client server serves every request with background datafile updates
- Batch event collection for efficiency
- LLM experiment and AI config testing capabilities
- Server-side processing for multiple users simultaneously
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 1 ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 14 | 0 |
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| Referring domains (Majestic) | 28 | 0 |
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