evalshipGarm Tech B.V.
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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
evalship helps engineering teams test LLM-powered software with a review of their evals at setup and a report on every pull request. The review checks scorers, judges and prompts for flaws, such as a judge that scores 1.0 when its call fails, and gives each flaw a fix with code references. Setup is a prompt for your coding agent: it configures GitHub Actions and opens a setup pull request. On later pull requests, evalship compares results with the default branch, reports the evals a change really broke and the likely cause, sets flaky evals aside, and flags changed prompts or LLM calls that no eval exercises. Its check can block a merge that breaks an eval. It reads results from pytest, Vitest, Jest, promptfoo, Langfuse, Braintrust and LangSmith, with no SDK to add. Evals run in the customer's own GitHub Actions with their own model API keys; evalship only reads the results. Teams get a dashboard with each eval's history and a weekly report by email. Public repositories are free.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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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 and founders shipping LLM features on GitHub.
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
$19/month
Free for all public repositories, plus 1 private repository with 1 user. Team is $19/month (3 users, 2 private repositories), Pro $49/month (10 users, 5 private repositories) and Business $199/month (50 users, 25 private repositories). Yearly billing gets 2 months free. Paid plans come with a 7-day free trial.
Free Version
Supported
Free Trial
Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationKayba
Founded: 2025
United States
kayba.ai/
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Company InformationGarm Tech B.V.
Founded: 2026
Netherlands
evalship.com
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Braintrust
Not Supported
GitHub Actions
Not Supported
Jest
Not Supported
LangSmith
Not Supported
Langfuse
Not Supported
Model Context Protocol (MCP)
Supported
Vitest
Not Supported
promptfoo
Not Supported
pytest
Not Supported
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Integrations
Braintrust
Supported
GitHub Actions
Supported
Jest
Supported
LangSmith
Supported
Langfuse
Supported
Model Context Protocol (MCP)
Not Supported
Vitest
Supported
promptfoo
Supported
pytest
Supported
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