| What it does | One-click molecular docking with AutoDock Vina in your browser
| 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 | Not given
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| Pricing | Not given
| 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 | - Automated receptor and ligand preparation via Meeko
- Batch screening up to 300 ligands per job
- Publication-ready PDF reports with embedded figures
- 2D and 3D interaction diagrams with PLIP
- PoseBusters automated pose quality validation
- ADMET analysis including Lipinski, Veber, and QED
- Custom docking box definition with 3D visualization
- Co-crystal redock validation against crystal poses
- Interactive 3D viewer for pose inspection
- Optional PyMOL publication-quality binding site rendering
| - 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 | - No software installation or local computing required
- Fully reproducible, documented pipeline with exact software versions recorded per job
- Automated Methods text and citations ready for manuscript submission
- Batch parallel docking with per-ligand failure tolerance
- Secure cloud processing with immediate data deletion after job completion
| - 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) | 3 ▲ +1 (up) since last check | 1 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 17 | 14 |
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| Referring domains (Majestic) | 9 | 28 |
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