Use cases
Solutions

Built for teams shipping AI in production

LinkAI Route helps teams manage API access, credits, and logs without building custom tooling.

01 · AI product teams

Multiple environments, shared keys, and hard-to-track usage make AI features brittle at scale.

Pain points

Inconsistent auth and logging across teams leads to slow debugging and unpredictable spend.

Rate limits and usage policies are hard to enforce across environments.

How LinkAI Route helps

  1. Isolate projects — separate production, staging, and experiments.
  2. Use one API — OpenAI-compatible requests with streaming.
  3. Trace everything — logs and usage by project and API key.
Example flow: Client → LinkAI Route → Provider → Logs & usage dashboard.

02 · Agencies & internal platforms

Teams serving multiple clients need per-project limits, billing clarity, and reliable logs.

Pain points

Usage per client is hard to attribute, and runaway spend can’t be controlled quickly.

How LinkAI Route helps

  1. Project isolation — one project per client with its own keys.
  2. Limits per client — RPM, concurrency, and daily caps.
  3. Export usage — CSV exports for invoicing and reporting.
Example flow: Client app → Project key → Gateway → Usage export.

03 · Ops & finance governance

Leadership needs predictable spend, audit trails, and clear limits for AI usage.

Pain points

Spend spikes are hard to trace, and teams lack a single source of truth.

How LinkAI Route helps

  1. Credits + ledger — balances and refunds tracked in Billing.
  2. Rate limits — cap RPM, concurrency, and daily usage.
  3. Audit-ready logs — request history with status and latency.
Example flow: Request → Credits ledger → Usage export → Finance reporting.

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