AI Control Center

Track and cut your AI provider costs in one dashboard

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September 2, 2026 Why I built AI Control Center (and what it actually does)

A few months ago our AI bill quietly crept up, and nobody on the team could tell you why.

We were using OpenAI, Anthropic, Gemini, and Bedrock at the same time. Every provider had its own dashboard, its own billing page, its own login. There was no single place to see total spend, and we only found out costs had gone up after the invoice landed.

On top of that, we kept defaulting to the most expensive model for almost everything — not because we needed to, but because nobody had the numbers to prove a cheaper model would work just as well for most requests.

And separately: API keys were scattered across .env files and Slack DMs. That's its own risk for any team.

So I built AI Control Center to fix both problems in one place:

— Real usage-based cost tracking across providers, pulled from actual usage logs, not estimates

— A reveal-once key vault (keys are shown in full exactly once, then only the last 4 characters are ever stored)

— Provider health monitoring with real uptime data, not guesses

— A cost optimizer that shows where you can realistically switch to a cheaper model without hurting output quality

— Team roles, 2FA, and audit logging for teams that need it

It's solo-built, still early, and free while I get feedback from real usage. I'd rather find out now what's actually useful versus what I think is useful.

If you're juggling more than one AI provider — how are you currently tracking what you're spending? Genuinely curious if this is a problem other teams have, or if we were just doing something wrong.

3 Comments

  1. 1
    The multi-provider cost problem feels like the strongest wedge. Are teams asking for cost visibility first, or safer API key management?
    1. 1
      Good question. From what I've seen (and from talking to early users), cost visibility usually comes first — teams don't feel the pain of scattered API keys until after they've already had a "wait, why is our bill this high" moment. Key management feels like a "nice to have, we'll get to it" problem until there's an actual security incident. That said, they're kind of linked — once someone's staring at a cost dashboard and asking "why is this provider spending so much," the next question is almost always "wait, who even has access to this key." So cost visibility is the hook, but key management is what keeps them around. Curious what you've seen on your end — has it been different for the teams you've talked to?
      1. 1
        That hook-versus-retention distinction is interesting. I’d rather compare notes on how teams are actually behaving than give you a shallow answer here. Happy to continue privately — what’s the best email to reach you on?

About

I built AI Control Center because our team was juggling separate dashboards for every AI provider we used — OpenAI, Anthropic, Gemini, Bedrock — and nobody had a single view of what we were actually spending.