Financial Services.
Every decision is logged with its inputs, model version and reviewer, so a credit committee or an examiner can replay it.
−63%
Loan-file review time
100%
Decisions with an audit trail
9 wks
Kickoff to production
02 · Where this fits
Key use cases
What teams in
Financial Services
build with us
An agent pre-checks completeness and financials, so underwriters start from a flagged file instead of a blank one.
Models score every transaction and route only the unusual ones, each with the signals that triggered the flag.
Source figures pulled and reconciled into the regulator’s template, with a reviewer sign-off before filing.
Account and policy answers grounded in your own documentation, cited, and refused when unsure.
03 · Governance
Built for review
Every decision is logged with its inputs, model version and reviewer, so a credit committee or an examiner can replay it.
SOC 2 Type II
Model risk management (SR 11-7)
Fair lending review
PCI DSS scope control
−63%
Loan-file review time
100%
Decisions with an audit trail
9 wks
Kickoff to production
05 · The services behind it
8–14 weeks
02
·
Agents
From
$65k
Agent & Workflow Automation
Production-grade AI agents that execute multi-step operational workflows, with human review where it matters.
See how it works
6–12 weeks
03
·
Knowledge
From
$65k
Knowledge & RAG Systems
Retrieval-augmented assistants that answer from your own documents, policies and systems of record, with citations.
See how it works
10–16 weeks
04
·
Documents
From
$65k
Document AI
Extraction, classification and routing pipelines that turn unstructured documents into structured, trustworthy data.
See how it works
06 · Questions
Asked by teams in this industry
Anything else, a 30-minute call covers it.
Q
Can the model explain a credit decision?
Q
How do you handle model risk review?
Q
Does customer data leave our environment?
Ready to see what this
looks like for your team?
A 30-minute call, scoped to the actual constraints of your industry, not a generic AI pitch.