Finance & Fintech
Financial institutions sit on some of the most valuable text and transaction data anywhere, and some of the strictest rules about where it can go. We deploy AI that respects both.
Why AI stalls in Finance & Fintech
Financial institutions face model risk management requirements, strict data handling rules and heavy scrutiny from examiners. Public AI APIs raise questions that are hard to answer: where the data is processed, how long it is retained, and how model changes are controlled. Many institutions pause AI adoption rather than risk an adverse finding.
How we make it work
Our typical deployment runs open-weight models inside the institution's data center or dedicated cloud tenancy, integrated with document management and core systems through permission-aware retrieval. Every prompt and response is logged, model versions are change-controlled, and documentation is prepared to support model risk management review under SR 11-7 style frameworks.
Where private AI pays off first
Credit memo drafting
Summarize financials and prior decisions into analyst-ready drafts.
KYC & AML review
Triage alerts and assemble case files from internal data.
Policy Q&A
Answer staff questions from internal policies with citations.
Call & chat analytics
Classify intent and compliance risk across customer conversations.
Regulatory change tracking
Summarize new rules and map them to affected internal policies.
Fraud investigation support
Assemble timelines and evidence from case notes and transaction data.
Frameworks we design around
We don't certify you, but we build and document systems so your compliance team can map them to the rules you answer to. Every deployment ships with an evidence pack covering data flows, access control, logging, model change management and incident response.
How we typically start
Private & On-Prem LLM Deployment
Run open-weight models on your own servers or private cloud, with no data leaving your network.
Explore service →SVC-06AI Security & Compliance Audit
Assess model risk, data privacy and controls before regulators or customers ask.
Explore service →SVC-05Custom Model Fine-Tuning
Adapt open models to your language, documents and workflows with your own data.
Explore service →Common questions
Can this pass our model risk review?
We provide the documentation model risk teams typically request: purpose, data, testing, limitations and monitoring. Approval remains with your institution.
Do you support core banking integrations?
Yes, through APIs, CDC or file-based feeds, depending on your core provider.
Find out what private AI would cost you.
A 45-minute call with an engineer, not a sales script. You'll leave with a rough architecture, a cost range and the next three steps.