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Know what AI costs. See what you get back.

Understand spending, share budgets and connect AI use to the work it supports.

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Buy tokens, rent GPUs, or own the rack?

Open-weight models are now good enough to make self-hosting a financial question rather than a capability one. I modelled four options, an office rack, colocation, rented GPUs and per-token APIs, to find where each one actually wins. The answer turns on utilisation, and it isn't the one the internet keeps giving.

Turn a $3m AI bill into $1.9m

Most teams overpay for AI twice without noticing: they run everything through the default flagship model, and they buy the tokens on a metered plan they can't see into. An intelligent proxy fixes both. Here is the maths, a calculator you can drag, and where Flowstate fits.

Start with the work All use cases

Understand AI spending and value

See where the budget goes and what the business gets back.

Share one AI budget across your tools

Fund people, teams and projects across connected services.

Give your team more capacity

Reduce the preparation, checking and follow-up around recurring work.

Connect AI use to delivered work

Follow AI activity into projects, code and business results.
Quick links
Flowstate / People + AI Talk through your priorities
Use cases

See who uses AI. Find the tools earning their place.

Understand who’s using AI, who needs help and which tools are no longer useful. Compare adoption across your teams and reclaim the cost of unused seats.

Talk through your AI spending

Find teams that need support.

See adoption by team and spot changes over time. Talk to the people doing the work before deciding whether they need training, a different tool or less access.

See F.AI scores and session evidence ↗
Active AI users · Last 30 days
Engineering 42 / 50
Marketing 18 / 24
Operations 12 / 30
Activity from connected tools

Compare the tools people actually use.

See the mix of tools within each team. Find overlapping subscriptions and ask whether another tool, more support or less access would help.

Connect AI use to work and projects ↗
Active users · Last 30 days
ToolEngineeringMarketing
Claude 42 12
ChatGPT 24 18
Gemini 9 8
People can use more than one tool

Recover the cost of unused access.

Identify former employees and inactive accounts with paid seats. Apply your suspension rules and track the costs you remove.

Review unused access ↗
Access review
AccountToolAction
Former employee Claude Auto-suspended
Inactive account ChatGPT Review due
Unused account Gemini Auto-suspended
Suspension follows your agreed access policy
Your systems, connected

Use the tools behind this work.

We agree which records, access and controls your workflow needs, then connect the relevant systems.

Explore all integrations ↗
Claude Enterprise Available ChatGPT Enterprise Discuss setup GitHub Copilot Available Microsoft 365 Copilot Available Gemini for Workspace Discuss setup

Measure what changes.

Track active access, lapsed usage, tool overlap and the cost of unused seats you remove. Assess capability and task performance separately with F.AI.

More control over your AI costs.

AI spending & value

Know where your AI budget goes. And what it’s doing.

 One budget across your AI tools

Give your people a budget. Let them choose the tools.

 Approvals & controls

Make AI spending someone’s responsibility.

Start with the costs you need to control.

Show us your tools and how you manage spending today.

Talk to Flowstate
Practical questions

What to know before you start.

Is more AI usage always better?

No. Usage shows activity. Compare it with the task, quality and cost, and use F.AI evidence to identify useful habits and support needs.

When does removing an unused seat save money?

It depends on the contract. Some cancellations reduce the next bill. Others avoid a renewal or a future purchase. Keep those outcomes separate.