Govern what your engineering team spends on Claude Code, before the invoice arrives.
AI TokenScope is currently built for engineering teams using Claude Code through supported launcher and proxy environments. It provides cost attribution, budgets, access controls, policy enforcement, and reporting. Additional providers, direct server-side APIs, CI/CD integrations, and broader production workloads are roadmap capabilities.
Built for teams with real AI usage to govern.
Engineering leaders, CTOs, founders, FinOps leaders, and platform teams whose engineers use Claude Code, with more than one person or team needing governed access and cost attribution.
Nobody can say what last month's bill will be until it arrives.
Claude Code usage is spread across team members and projects, with no per-developer or per-team attribution.
One test script ran up a four-figure bill overnight.
No budget or rate limit stopped it before the request went through, only the invoice caught it after.
Access outlives the person who needed it.
Developer tokens and seats get provisioned faster than they get revoked when someone changes roles or leaves.
Visibility, controls, and a paper trail on AI spend.
A review of your current AI cost exposure and governance gaps, followed by AI TokenScope as the tool that closes them.
AI TokenScope currently governs engineering teams using Claude Code in supported launcher and proxy environments. Prompt caching for Claude requests is part of the picture — repeated requests can be cached to cut redundant token cost without changing what the request returns. Support for additional AI providers and direct server-side API workloads is on the roadmap.
AI TokenScope
AI TokenScope
Engineering teams using Claude Code day to day, with no per-developer visibility into what's being spent or on what.
Claude Code requests are tracked and attributed per developer and project, with spending limits enforced before a request goes through rather than discovered after the invoice.
Automated cost reports, per-person access revoked in seconds, and prompt caching that reduces repeat token cost.
What's coming after Claude Code.
Additional AI provider support (OpenAI, Gemini, and others)
Direct server-side API workload governance
CI/CD pipeline integrations
Additional operating systems and launcher environments
Broader production API workload coverage
None of the above are currently available. They are planned and subject to change.
For decisions a dashboard can't make on its own.
Some AI cost questions are architectural or strategic, not something a usage dashboard resolves by itself: build vs. buy, which provider to standardize on, or how to structure access as the team grows.