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LLM FinOps, AI governance, model benchmarks, and building in public — written by engineers, for engineers.
You received a $14,000 OpenAI invoice. Engineering says it's the search feature. Product blames the summarization pipeline. The reality? Nobody actually knows. Here's how that happens — and how to fix it with token-level attribution.
Provider leaderboards use academic benchmarks. We ran 200,000 tokens of actual enterprise workloads — code generation, document summarization, structured extraction, and multi-turn chat — through all three. The results surprised us.
The EU AI Act isn't just a compliance checkbox — it's a structural change to how you build, document, and deploy AI systems. Here's what every engineering team needs to know before the August 2026 deadline for high-risk AI systems.
A 45-person AI startup was spending ₹39 lakhs/month on LLM APIs with no idea where it was going. After deploying TokenFin, they had attribution data in 20 minutes. Two weeks later, their bill was ₹23L. Here's exactly what they found and what they did.
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