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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2 solutions
vllm-ai-spend-control-for-smb-agent-workflows
Small businesses running agents on self‑hosted vLLM struggle to see aggregated LLM spend per customer, team, or use case. Without built‑in budgeting, a runaway prompt or misconfigured agent can balloon compute costs before anyone notices.Track, cap, and forecast LLM costs across all your agents powered by self‑hosted vLLM models, without slowing down responses.
agnostic-agent-feedback-loop-for-fine-tuning
A boutique marketing agency uses an AI agent to generate ad copy. The agent often misses the brand voice, requiring manual edits. The agency wants to capture these corrections and use them to fine-tune a smaller, cheaper model that better matches their style. They need a system that logs agent outputs, captures user feedback (accept/reject/edit), and periodically exports a clean dataset for fine-tuning. This reduces reliance on expensive API calls and improves quality over time.Collect agent decisions and user corrections to build a dataset for model fine-tuning.