SOLUTION · FINANCIAL SERVICES
Financial Services
Faster decisions your regulator can still follow. Every conclusion links back to its source, the system runs in your VPC or on-prem, and document review drops from days to hours.
Hours not days
Document review and risk analysis cycle
100%
Conclusions cited to source
VPC / on-prem
Deployment, data never leaves your domain
Move faster and keep the audit trail
The question for a bank was never whether AI can do the work. It's whether you can hand the output to compliance and audit with a straight face. Due diligence, contract review, and KYC/AML screening pile up hundreds of documents, and your analysts burn more time pulling files and hunting clauses than making the call. Bring in a black-box model and you swap that for a worse problem: you can't tell the regulator why it reached its conclusion. Accuracy, explainability, and data residency start to feel like a choose-two.
We don't sell you a tool and wish you luck. We embed engineers inside your environment, sit down with compliance, risk, and IT, and break the workflow into steps you can verify. Every AI conclusion carries the source passage, the cited page, and the reasoning behind it, so an analyst sees it, audit checks it, and a regulator can follow it back. The system runs in your VPC or on-prem. Your data never leaves your domain.
We use RAG to tie the model to your own documents and policies instead of letting it improvise, and we govern model risk with human-review gates, confidence scores, and reproducible audit logs. Delivery moves in weeks. You typically have a working system running on real files within two weeks, not a slide deck.
How it works
Faster decisions your regulator can still follow. Every conclusion links back to its source, the system runs in your VPC or on-prem, and document review drops from days to hours.
Document pipeline
Risk routing
Capabilities
An audit trail you can follow
Every conclusion links back to the exact source passage, page number, and timestamp, and we keep the model's reasoning steps so compliance and audit can review each item and reconstruct the full decision path for a regulator.
VPC or on-prem, data stays home
The whole system deploys inside your private cloud (VPC) or data center, keeping documents, vector indexes, and model calls within your network boundary to meet data-residency and cross-border transfer rules.
Document review and risk analysis in hours
The repetitive extraction, comparison, and flagging work in due diligence and contract review runs automatically, so a several-hundred-page file gets a first pass in hours and analysts focus on judgment and exceptions.
RAG tied to your policies
Retrieval-augmented generation binds the model to your own clause library, internal policies, and past cases, with every answer citing its source, which shuts down fabrication and lowers model risk.
Human-review gates and confidence scores
High-risk items are flagged with a confidence score and routed for human sign-off, establishing an AI-drafts, human-decides workflow so the model never issues a final ruling unsupervised.
KYC/AML screening and exception handling
Beneficial-ownership structures, sanctions lists, and adverse media are screened automatically, with hits packaged into reviewable cases that free analysts from drowning in false positives.
Delivery cadence
- 01
WEEK 1
Embed and map the workflow
Engineers embed and, alongside compliance, risk, and IT, pick the first high-value workflow, inventory document types, data-residency requirements, and audit standards, and define verifiable success metrics.
- 02
WEEK 2
MVP on real files
Deploy the RAG pipeline and review interface in your VPC or on-prem environment and produce a first working result on real (de-identified) files, not a slideware PoC.
- 03
WEEK 3-4
Harden for audit and tune
Tune prompts, citation granularity, and confidence thresholds against analyst and audit feedback, complete the audit trail and access controls, and stand up the human-review gates.
- 04
WEEK 5+
Go live and scale
After compliance sign-off, go live and extend the same framework to other lines of business, with operations runbooks and knowledge transfer to your internal team.
Use cases
01
M&A due diligence
Ingest the hundreds of contracts, financials, and disclosures in a data room at once, auto-extract key terms, surface change-of-control, non-compete, and contingent-liability clauses, and output a cited risk list for counsel and the deal team to review.
02
Contract and clause review
Benchmark against your standard clause library to flag terms that deviate from standard, missing protective covenants, and unfavorable language, with side-by-side comparisons and suggested redlines.
03
Credit and investment risk analysis
Pull metrics from financial statements, credit reports, and industry data to produce a structured risk summary and red-flag list, with every figure linked back to its source.
04
KYC/AML customer due diligence
At onboarding and periodic review, automatically compile beneficial ownership, sanctions and PEP screening, and adverse media into a cited case file flagging items that need a second look.
05
Regulatory inquiries and evidence response
When a regulator or internal audit asks, pull supporting evidence from policy documents and case records and draft a cited response, cutting the time it takes to substantiate a position.
FAQ
Yes. Every conclusion carries the source passage, cited page, and reasoning, so compliance and audit can review each item and reconstruct the full decision path. We break the workflow into steps you can verify rather than black-box output, so you can show a regulator why the model reached its conclusion.
No. The whole system can deploy in your VPC or on-prem data center, keeping documents, vector indexes, and model calls within your network boundary. That lets you meet data-residency and cross-border transfer rules, so sensitive files never get shipped to a third-party cloud.
We anchor the model to your own documents and policies with RAG, and every answer cites its source, which shuts down unsupported fabrication. High-risk items are flagged with a confidence score and routed for human review, creating an AI-drafts, human-decides split so the model never makes a final ruling unsupervised.
Yes. We are model-neutral and can connect Anthropic, OpenAI, or on-prem open-source models inside your environment, chosen to fit your data-residency and cost requirements. All model calls happen within your deployment boundary.
You typically have a working MVP running on your real (de-identified) files within 2 weeks, not a PoC slide deck. The first high-value workflow usually reaches compliance sign-off in 4 to 6 weeks, after which we extend the same framework to other lines of business.
No. The goal is to free analysts from the repetitive file-pulling, comparison, and flagging so they focus on judgment and exceptions. The system drafts and organizes, while final decision authority and the review gates always stay in human hands.
AI workflows,
built into your operations
We deploy forward — FDE and FDM — to build the AI agents and workflows your team runs on. Live in weeks, not quarters.