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
anthropic-llm-observability-for-smb-ai-operations
Small businesses using Anthropic's Claude models for customer support or content generation lack visibility into token spend, latency patterns, and sudden error rate changes. Without integrated observability, they overspend and cannot diagnose issues before customers complain.Drop-in OpenTelemetry instrumentation that gives SMBs real-time cost, latency, and error insights across all Anthropic API calls, plus pre-built dashboards for Langfuse and Phoenix.
agnostic-per-tenant-llm-cost-chargeback
The VP of Engineering at a B2B vertical SaaS company needs to bill each SMB customer for the AI features they use. Without per-tenant cost tracking, the company absorbs all LLM expenses, eroding margins. Existing observability tools don't tie token usage to tenant IDs, making chargeback impossible. The team manually approximates costs, leading to billing disputes and lost revenue.Attribute every LLM call to the right tenant and export cost data to your billing system.