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Helm

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
Helm / Workloads and agents

Know what it costs to put AI to work.

People using AI tools are only part of the picture. Track the AI inside your applications and the agents carrying out jobs for your business.

Talk through your workloads ↗
Workloads

AI inside an application.

A support reply, document search or product recommendation. Follow request volume, model use, running cost and the cost per successful result.

Support assistantIllustrative month
Replies generated2,400
Running cost$720
Cost per reply$0.30
Compare quality and resolution alongside cost. A generated reply is not automatically a resolved customer problem.
Agents

AI carrying out a job.

A reporting agent or a contract preparation flow. Follow completed runs, checks, exceptions, human decisions and the cost per completed job.

Reporting agentIllustrative month
Completed jobs40
Running cost$120
Cost per job$3.00
Track human review separately. Waiting for an answer, a failed run and a completed job are different outcomes.

The same investment. Different measures.

Keep Workloads and Agents as separate views in Helm. Attribute each to its owner and project, then compare the cost with the result it produces. Available measures depend on the connected systems and the evidence they provide.

See how agents, data and views work together in Sail ↗
Practical questions

What to know before you start.

What is the difference between a workload and an agent?

A workload is AI running inside an application, such as generating a support reply. An agent carries out a job through a sequence of steps, such as preparing a report and asking for approval.

Which cost metric should we track?

Choose a useful completed result. For an application that might be a resolved query. For an agent it might be an approved report. Include failed attempts, model costs and human review when comparing alternatives.