Self-hosted Prometheus exporter for LLM usage, token, request, and USD cost telemetry across OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and AWS Bedrock.
See what your AI coding cost and produced, from the logs already on your disk. Offline, no account.
Production-tested AI/ML architecture patterns for regulated enterprises. 18 patterns covering AI gateways, multi-agent pipelines, compliance-aware routing, governance-as-architecture, and more. Each pattern includes architecture diagrams, tradeoffs, NIST AI RMF mapping, and quantitative governance metrics. Built from 18+ years in healthcare IT
Open-source LLM FinOps proxy — track OpenAI, Anthropic (Claude), and Google Gemini costs by feature, team, and customer. Zero code changes. pip install burnlens.
Govern every euro your AI spends. Cross-provider metering, budgets, policy enforcement, chargeback, forecasting and cost‐aware routing for Laravel — the FinOps/governance brick for AI agents.
A production token hygiene system for AI-assisted development workflows. Built after a 60.8M token burn on May 16 2026. Model routing, prompt caching, session discipline, and cost operations for Claude Code.
Token-Light, Code-Intensive (TLCI) — A design philosophy for AI agent automation. Use AI only where it's needed. 80-97% cost reduction.
AI Governance: The Foundation for Organized AI in Production — A Field Guide by Fabio Bastos. Published under CC BY 4.0.
Open-source LLM FinOps proxy — track OpenAI, Anthropic (Claude), and Google Gemini costs by feature, team, and customer. Zero code changes. pip install burnlens.
Open-source AI token savings audit primitive. Apache 2.0. Tamper-evident JCS-canonicalized SHA-256 attestations over paired-run logs. Zero runtime dependencies.
FinOps governance layer for enterprise AI spend. Token-level cost attribution, multi-provider price comparison, budget burn-down, anomaly detection, monthly forecasting with confidence intervals, and department chargeback rollups.
Open-source FinOps Operating System for AWS, Azure, GCP, Kubernetes, and AI workloads. Includes governance frameworks, cost allocation models, KPI libraries, FOCUS standards, optimization playbooks, dashboards, automation patterns, and real-world case studies.
VP / Head of AI Engineering portfolio — 14 production AI demos, governance-first architecture. prasadkavuri.com
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