Practical writing from the team building ATP Token — on governance, usage accounting, and running many models with one key.
Latest
Token based pricing for finance leads: a 40-person seat vs token cost comparison, break-even math, a credits chargeback model and a monthly AI budget worksheet.
Shadow AI is employees using AI tools, accounts or API keys without IT approval. 5 examples, 2025 IBM and Verizon data, how to detect it and replace it.
GET /v1/models lists what an LLM platform offers; a model allowlist decides what a key may call. Request and response examples, the 403, and allowlist design.
OpenRouter alternatives compared: what OpenRouter charges, how its budgets and allowlists work, and when LiteLLM, Vercel AI Gateway or ATP Token fit better.
What an LLM gateway does, and how six gateways compare on hosting, pricing model, spend limits, model allowlists and API formats as of October 2026.
An OpenAI-compatible API lets the OpenAI SDK call Claude, Gemini and DeepSeek. When direct OpenAI is enough, when a gateway helps, and the code change.
Claude Code cost averages about $13 per developer per active day. A 25-developer budget worked out, plus 10 controls that keep agent spend inside a ceiling.
AI API spending limits compared: how OpenAI usage limits, Claude workspace caps, OpenRouter, Vercel and ATP Token behave at the limit, with a worked budget.
API key management for LLM APIs: what breaks with a shared key, how to issue one key per project, where each key lives, and a 30-day migration runbook.
LLM cost optimization for enterprises: four layers of AI cost management, 10 levers with sourced or worked effects, model choices by task, and a 30-day plan.
AI agent cost grows with every step because the whole context is resent. A 20-step agent priced at list rates, and five levers that cut the agent tax.
LLM cost often jumps after launch because prompts grow. A RAG bot going from 2k to 9k input tokens adds $25,200 a month. Five control gaps and a 5-day fix.
LLM token cost explained: the per-request formula, one request priced on 5 models, input vs output ratios, cached and reasoning tokens, and how to read a bill.
AI governance checklist for model API usage: 12 checks with an owner, a done criterion and audit evidence for each, mapped to the NIST AI RMF framework.
Start with a project key, or browse model rates first.
