Related Products
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About
Kayba makes AI agents self-improve from experience. It learns from an agent’s execution traces to detect failures, fix them, and measure whether the fix actually worked. Instead of relying on generic evals that cannot explain why an agent failed, Kayba derives failure modes from the agent’s own traces and builds custom benchmarks for the user’s domain, so teams can measure improvement against real production failure patterns. Kayba wires tracing into an agent with one line of setup, watches it around the clock, and flags the moment a step stops being recorded. Even good tracing rots as teams ship changes, and steps can quietly stop being captured; Kayba checks the tracing users already have, shows exactly what is broken, points to the file that needs attention, and sends the gap to a coding agent through MCP. The coding agent patches the issue, and Kayba verifies that the trace is actually closed.
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About
Papaya is the optimization engine for AI agents. Engineers connect their agents via SDK, and Papaya analyzes production traces to find improvements across context, prompts, prompt caching, subagents, and tool calls. It delivers actionable recommendations ranked by quality, latency, and cost impact, with the production runs that produced each finding. Approved improvements can be pushed to production as pull requests. Papaya runs more than 200 research-backed analyses and typically finds a 10%+ quality improvement on the first workflow analysis.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
AI development teams that need to diagnose agent failures, generate reviewable fixes, and track whether those fixes improve performance over time
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Audience
Engineering teams operating production LLM agents and agentic workflows
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationKayba
Founded: 2025
United States
kayba.ai/
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Company InformationPapaya
Founded: 2026
United States
papaya.fyi/
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Alternatives |
AlternativesNo Alternatives
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Categories |
Categories |
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Integrations
Model Context Protocol (MCP)
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