Kamya Shah

TL;DR * Provider invoices group spend by API key or project, so tracking LLM usage by team requires attribution upstream of the provider. * Bifrost virtual keys attach to one team or one customer, and every request is priced and logged with that team identity. * Bifrost Prometheus metrics carry team_id,

TL;DR * Controlling LLM access across teams means authenticating each caller, authorizing which models and tools that caller may reach, and recording the decision, enforced on the request path rather than in application code. * Controlling access per team takes five controls: scoped credentials, identity sync, separation of permission from visibility,

TL;DR * Gateway-level PII redaction detects sensitive values in an LLM request and rewrites them before the request leaves your network, so no application has to sanitize its own prompts. * Bifrost implements this through guardrails: rules written in Common Expression Language decide when to evaluate, and profiles decide how,

TL;DR * AI agent skills are reusable SKILL.md folders that give coding agents like Claude Code and Codex domain-specific instructions, and teams accumulate dozens of them fast once more than one person is writing skills. * Bifrost's Skills Repository lets a team create, publish, and version agent

TL;DR * Adaptive load balancing distributes AI traffic across providers and API keys using live performance data instead of a fixed weight or round-robin rule. * Bifrost Enterprise recalculates route weights every 5 seconds from error rate, latency, and utilization, adding less than 10 microseconds to routing overhead. * Routes move