Solutions
Production-grade solutions that turn our open-source packages into deployable AI systems for specific business problems. Pick one, follow the DIY tutorial to see how it's done, download the examples and deploy them on your own infrastructure — for free — or tell us which ones you want customized and deployed.
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5 solutions
agnostic-recruiter-resume-scoring-agent-2
A solo recruiter at a 5-person firm spends 6+ hours per role manually scoring 50-200 resumes against a rubric. Inconsistent scoring leads to missed top candidates and client complaints. Enterprise ATS scoring tools are too expensive and complex. The recruiter needs a fast, fair, and auditable way to rank candidates without hiring more staff.Score 200 resumes per role in seconds with a consistent rubric, no spreadsheets.
openai-agent-eval-harness-for-smb-customer-support-quality
SMB customer support agents powered by OpenAI often drift in tone, hallucinate product details, or miss steps, but manual spot-checking doesn't scale as ticket volume grows.Automatically evaluate every production AI support interaction to catch bad answers, hallucination, and policy violations before they affect customers.
databricks-agent-eval-harness-for-smb-support-bots
SMBs deploying AI support agents struggle to catch regressions before they impact customers, leading to poor responses and handoffs. Manual QA is costly and inconsistent.Automated regression testing for SMB customer support agents, running on Databricks with BrainsTrust analytics.
vllm-agent-eval-harness-for-fine-tuned-model-quality
SMBs that fine-tune open models locally lack a structured way to verify model quality before production, exposing them to regressions and failed customer interactions.Automated CI/CD-quality evaluations for locally-hosted fine-tuned LLMs using vLLM with LLM-as-judge and cost tracking.
anthropic-eval-harness-for-agent-quality-assurance
SMBs shipping customer‑support or sales agents on Anthropic’s models see quality drift over time—toxic phrasing, hallucinated facts, or missed tools—but lack a repeatable test suite to catch these regressions before they reach users.Continuous regression testing and safety scoring for Anthropic‑powered agents, with automated quality gates before any customer‑facing deployment.