Speed is easy. Explaining the decision eighteen months later is the hard part.

Decided before any code is written and documented in the agreement. Options range from enterprise API tiers with contractual no-training terms and a specified region, through self-hosted embeddings and vector storage inside your own VPC, to fully local models where nothing leaves your perimeter at all.

For most regulated clients the answer is self-hosted retrieval with a contracted model provider, or fully local where the data classification demands it.

You get an evidence pack, not a promise: the model card and version history, the evaluation methodology and results, the confidence thresholds and how they were set, the escalation rules, and the immutable decision log with retention aligned to your policy.

Any individual decision can be reconstructed end to end — which documents were retrieved, what the model produced, what score it carried, and what the human did with it.

It only answers from retrieved documents, and the citation is generated from the retrieval, not from the model's memory — so a claim without a source can't reach the analyst. Anything below the confidence threshold is escalated rather than shown as an answer.

Then it's measured: an evaluation set built with your own team, run before deployment and continuously afterwards, so a degradation shows up as a number rather than as an incident.

Possibly, depending on the use. Creditworthiness assessment is explicitly high-risk; internal knowledge retrieval that recommends to a human generally is not. The design choices on this page — human decision authority, logging, transparency, human oversight — are deliberately aligned with the high-risk obligations regardless, because building to the stricter bar costs little and keeps your options open.

I'm an engineer, not counsel. Your legal team makes the classification call; I build so that whichever way it lands, the controls are already there.

An honest answer: in the deployments this is modelled on, headcount doesn't fall — throughput rises and the work changes shape. Analysts stop assembling and start deciding, which is both the higher-value half and the part they were hired for.

If your actual goal is headcount reduction, say so at the start. It changes what we build and how it's measured, and I'd rather design for the real objective than discover it in month three.

Sometimes it doesn't, and that's a reasonable outcome — some institutions require a corporate counterparty and I'll say so early rather than waste your procurement cycle.

What I can offer: everything runs in your infrastructure and your accounts, all code in your repositories, no proprietary runtime and no dependency on me continuing to exist. Handover and documentation are contracted deliverables, not goodwill. For many mid-sized fintechs that's a lower concentration risk than a vendor whose product you can't inspect.