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
google-gemini-ai-spend-control-for-smbs
SMBs adopting Google Gemini for AI face unpredictable per-token costs and risk overspending without centralized visibility or automatic guardrails.Real-time LLM cost tracking and budget enforcement for Google Gemini-powered SMB applications.
agnostic-ai-budget-control-for-smb-agent-workflows
SMBs adopting multiple AI agents across customer support, sales, and operations face unpredictable API costs. Without a provider-agnostic budget, it's easy to overspend or lock into a single vendor.Real-time spend enforcement and cost-aware routing across any LLM provider for small business AI agents.
aws-bedrock-cost-control-for-serverless-ai-applications
SMBs adopting AWS Bedrock for AI features often see unpredictable costs because there's no native spend controls. A single mis‑sized prompt or a spike in traffic can burn through a month's budget in hours, with no granular insight into which model or user caused it.A budget‑aware middleware that routes, caps, and tracks every AWS Bedrock LLM call, preventing surprise bills for SMBs running serverless AI features.
vertex-ai-budget-guardrails-for-multi-agent-systems
Small businesses using multiple AI agents on Vertex AI often exceed their monthly budget due to unpredictable model calls and no per-agent cost controls.Keep your AI costs predictable with per-agent budget limits and automatic model routing on Vertex AI.