Kuldeep Paul

LiteLLM has served as the default open-source option for teams looking to unify access across multiple LLM providers. Its Python-based proxy translates API schemas from providers like OpenAI, Anthropic, and AWS Bedrock into a standardized OpenAI-compatible format, making it a practical starting point for prototyping and early-

Claude Code adoption is accelerating across enterprise engineering organizations. Anthropic reports that the tool averages approximately $6 per developer per day on API pricing, with team-level costs landing between $100 and $200 per developer per month on Sonnet. For a 200-person engineering team, that is $20,000 to

Compare the best LLM gateways for monitoring Claude Code token spend, with per-developer cost tracking, budgets, and real-time token usage visibility. A single Claude Code session can issue hundreds of model calls across Sonnet, Opus, and Haiku, and without a gateway in front of it, that Claude Code

Claude Code is Anthropic's terminal-based AI coding agent. Out of the box, it connects to Anthropic's API and uses Claude models exclusively. This works well for many use cases, but production engineering teams often need more flexibility: the ability to route Claude Code traffic through

As production AI applications scale, two infrastructure challenges dominate engineering budgets: redundant LLM API calls and inefficient provider routing. Organizations running high-volume inference workloads routinely overpay due to repeated queries hitting provider APIs instead of being served from cache, and static routing configurations that ignore real-time provider performance.