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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4 solutions
ollama-agent-eval-harness-for-on-prem-smb-support-qa
SMBs running on-prem LLMs with Ollama lack automated QA to catch regressions in agent performance before customers encounter errors, leading to support drift and quality degradation.Run continuous quality evaluation on local AI agents using Ollama, with regression gating and cost tracking, all from a CLI.
xai-grok-agent-eval-harness-for-smb-support-qa
Small businesses using xAI Grok for customer support agents have no automated way to verify response quality across prompt changes, model updates, or conversation scenarios. Manual spot-checks miss regressions, leading to incorrect answers, safety issues, and lost trust.Continuously evaluate your xAI Grok-powered customer support agents to catch regressions before they affect customers.
agnostic-customer-feedback-triage
A 25-person B2B SaaS company receives hundreds of pieces of feedback each week via support tickets, NPS comments, and sales calls. The product manager manually reads through a fraction of them, often missing the most requested features or the most painful bugs. This leads to a product roadmap that doesn't align with customer needs, increasing churn. They need an agent that ingests all feedback sources, deduplicates, clusters by topic, estimates the number of affected accounts, and generates a weekly report of the top 10 most impactful product changes. This ensures the product team works on what matters most to retention.Turn support tickets and NPS comments into prioritized product suggestions.
langchain-agent-eval-harness-for-small-business-reliability
SMBs deploying AI agents have no way to systematically test if updates or new prompts break business-critical tasks, leading to customer-facing errors and trust erosion.Continuous evaluation of your AI agents using LangChain and REAA's eval harness suite to ensure reliable business outcomes.