AI features
Where the quality bar actually sits
Scorith is in the business of building a core AI/ML product for LLM quality. Named jobs: traces, datasets from live misses, graders in CI, and red-team packs. It observes and grades agents (LangChain, LangGraph, homebrew). It does not act as one.
AI feature · Live traces to datasets
Every LLM and tool call becomes a gold row
For teams drowning in production misses with no labeled set
Drop the SDK. Inspect agent trees, tool calls, cost, and latency on a single span. Pull live misses into a dataset. Product can add rows from the studio without waiting on a dump.
SDK span → POST /v1/traces → labeled dataset
AI feature · Graders in CI
The suite comments on the PR against main
For engineers who refuse a silent quality drop
Metric families you version in git. Scorith comments on the PR with the delta against main. The suite holds, or the merge waits. Same suite on a nightly sample.
PR → POST /v1/suites/{id}/run → GET /v1/suites/{id}/delta
AI feature · Red-team packs
Adversarial chats and a packet compliance can read
For regulated desks that need a named owner and a calendar
Red-team agents so every release shares one quality bar. Adversarial chats and PDF-ready risk notes. A calendar, a pack, a named owner.
Pack → adversarial runs → risk notes
AI feature · Model-backed graders
Claude, GPT-4o, Gemini 2.5, Llama 3 70B, Mistral Large
For platform teams scoring LangChain, LangGraph, or homebrew agents
Planned model families: Claude 3.7 Sonnet, GPT-4o, Gemini 2.5, Llama 3 70B, Mistral Large. Access: Bedrock, Anthropic, OpenAI Direct, Hugging Face. Scorith is not fine-tuning those models.
Span sample → selected grader model → score on the hall
AI development tools / APIs. Machine learning, compliance, cybersecurity. MVP stage — no invented customers, funding, or uptime claims on this page. Scorith grades LLM products; it does not replace them.