T-Llama lets employees keep the AI tools that make them productive while the company gets identity-based access, keyless endpoints, live budget enforcement, and metadata-first evidence over every governed request.
Developers and staff no longer need provider API keys in shell profiles, tool configs, repos, or CI. T-Llama gives tools a scoped local credential and keeps provider keys inside the gateway boundary.
Bans create shadow AI. Mandated chat boxes kill the workflows that made AI valuable. T-Llama meets users where they already work: Claude Code, Codex, and OpenAI- and Anthropic-compatible clients.
T-Llama evaluates budgets before requests spend provider tokens. Finance gets project and user attribution, remaining budget visibility, and cost confidence instead of a surprise provider invoice.
A public endpoint protected only by a bearer token is still a public spend path. T-Llama is designed around private gateway reachability and fail-closed behavior when the private path is unavailable.
T-Llama records who used which tool, model, project, and budget outcome without storing raw prompts or completions by default. Compliance gets evidence; employees avoid a new prompt surveillance system.
Admins create projects, add members, allow models, set budgets, and see usage from an Entra-protected portal. Changes take effect on the next request because the gateway revalidates central policy every time.
Keyless endpoints, pre-egress guardrails, private gateway access, distinct failure classes, and identity-bound enforcement.
Budget enforcement before spend, project/user/tool attribution, cost confidence, remaining budget visibility, and analytics APIs for billing integration.
One control plane in front of models and providers, native tool adoption, API-first management, deterministic contract tests, and a simple pilot deployment shape.
Metadata-first evidence, Entra-based access, admin role gating, and no default prompt or completion capture.
Keep Claude Code, Codex, and compatible AI clients. Stop juggling provider keys. Launch tools through the Onramp and keep working.
A factual map of AI usage: who is using it, where spend lands, which tools and models matter, and where policy friction appears.