Applied AI and automation
Models put to work inside a real process: auditing, document handling, decision support, agents that do the repetitive part. We build it, then we prove it against your data.
The problem this solves
A process eats hours and nobody can say exactly how many. Someone has suggested AI. The risk is buying a platform before anyone has established that the process is automatable, what good looks like, or what it currently costs.
Who this is for
Businesses with a repetitive, high-volume, rule-heavy process and enough of their own data to measure against. If the process is undefined, that is the first piece of work, not a reason to skip measurement.
What you receive
A baseline of how the work is done today, a working automation for one process, an evaluation against that baseline on your own data, a human-review path for the cases it should not decide alone, and a written recommendation — including the recommendation not to proceed, if that is what the numbers say.
What we need from you
A representative sample of real data, permission to use it, and someone who does the work today and can say when an output is wrong. Without that last person there is no evaluation, only a demo.
Evidence
Internal builds and prototypes. We run our own automation and our own retrieval systems, and that is what the judgement here comes from. No client deployment is published yet, and we are not going to describe one that is not.
Costs beyond our fee
Model API usage is charged per token by the provider and scales with your volume — it is an ongoing operating cost, not a one-time fee, and it is not included in the build price. Vector storage, document processing and any SaaS the workflow touches are billed separately. An unknown usage charge is not zero, and we will estimate it with you rather than leave it out.
Timeline and what it depends on
Six weeks for a focused pilot, assuming the data and the reviewer are available from week one. Data access is the dependency that slips most often, and it usually slips on permissions rather than on engineering.
Support after delivery
A pilot ends with a report, not a running service. Taking it into production is a separate scope with its own operating agreement, monitoring and cost.
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