Trust center · Architecture
How See The Greens works
For: Operations leaders, production managers, processing supervisors, and IT integration leads.
Not for: Software engineers wiring MCP tools or Kubernetes — see Powered by ClawQL below.
What you get
See The Greens is a loan origination system built around one idea: catch document and compliance issues when files arrive, not weeks later in post-close QC.
Your team still makes every credit and underwriting decision. The system handles repetitive work — reading documents, checking them against investor and agency rules, organizing the file room, and opening conditions when data says something needs attention.
| Role | What changes |
|---|---|
| Processors | Review exceptions (large deposits, missing pages, guideline mismatches), not every upload |
| Underwriters | Work from a cleaner file with pre-validated extractions and a clear condition list |
| Ops / QC | Audit trail starts at intake, not after closing |
| IT | One API surface for documents, workflows, and notifications instead of a patchwork of OCR vendors |
A loan file, step by step
Below is a representative purchase-money workflow — the same pattern shown on the homepage (Loan #4821, bank statement, large deposit → Letter of Explanation).
Mortgage-first today. Auto, BNPL, and commercial use the same document and rules engine with different guideline packs — not a separate product rewrite.
Example: large deposit on a bank statement
This is the workflow buyers ask about most often.
- Upload — Processor or borrower drops
BankStatement_Jan2026.pdfon the loan. - Extract — System reads transaction lines and balances (not just OCR text).
- Validate — A deposit of $48,500 on Jan 14 exceeds your configured threshold.
- Recommend — UI shows: Income verified against W-2 and paystub ✓ and Large deposit detected ⚠.
- Condition — Letter of Explanation is auto-added with the extracted amount and date pre-filled.
- Human — Processor accepts, modifies, or rejects — then clears the condition when the LOX is on file.
No one waited for a QC sample. The exception surfaced in real time.
What AI does — and does not do
| AI handles | Your licensed staff handle |
|---|---|
| Document classification and renaming | Credit decisions and approvals |
| Field extraction (W-2, paystub, bank stmt, tax returns) | Final underwriting sign-off |
| Guideline checks against configured overlays | Exceptions that need judgment |
| Condition suggestions from extracted data | Clearing conditions and file status |
| File-room hygiene (versions, categories) | Client communication and disclosures |
Human-in-the-loop is default, not an upgrade tier. When confidence is low or policy requires it, work routes to a review queue before the loan moves forward.
How this differs from legacy LOS + bolt-on OCR
| Topic | Typical legacy stack | See The Greens |
|---|---|---|
| Document intelligence | Batch OCR or manual indexing | Validated on upload against your overlays |
| Conditions | Template checklists + manual entry | Generated from extracted fields and loan data |
| File room | Processors rename and sort | Self-organizing categories and version control |
| Memory across sessions | Often lost between tools or users | Persistent loan context for the file |
| Audit | Mutable logs, sample QC | Tamper-evident activity record per touch |
| Automation changes | IT release cycles | Ops-configurable rules for most workflow changes |
| Future agent tools | Siloed vendor APIs | Unified gateway — same APIs for people and approved automations |
Integrations (IT view)
See The Greens is designed to sit in a modern lender stack, not replace every system on day one.
Integration model: REST APIs and webhooks with role-scoped credentials. Your team defines which systems may read loan data vs write conditions or documents.
For a technical integration workshop, request a demo with your stack diagram.
Deployment options
| Model | Best for |
|---|---|
| Managed cloud | Fastest time to value; we operate the platform; you configure rules and integrations |
| Dedicated / VPC | Stricter data residency or network isolation — your loan data never touches shared infrastructure; we operate dedicated compute and storage in your contracted region |
| Self-hosted | Maximum control; your infrastructure team runs the environment with our reference architecture |
Frequently asked questions
What happens if AI gets it wrong?
When extraction confidence falls below your threshold, the loan routes to a human review queue before proceeding. AI recommendations are logged alongside human decisions — accepted, modified, or rejected — so you can audit every override.
Do we have to replace our current LOS on day one?
Many lenders start with document intelligence and condition automation alongside an existing LOS, then expand. Migration planning is part of onboarding.
Can we use our own investor overlays?
Yes. Guideline and investor rules are configurable — not hard-coded to a single investor.
What document types are supported out of the box?
W-2s, paystubs, bank statements, tax returns, IDs, purchase agreements, and common mortgage attachments. Custom types use the same pipeline.
How long does implementation take?
Most pilots go live within 2–4 weeks. Full production rollout with multiple investor overlays and integrations typically takes 6–10 weeks, depending on scope.
Powered by ClawQL
See The Greens is built on ClawQL — an orchestration platform for production-grade document processing, workflow automation, and audit in regulated environments.
Merkle audit trail, in plain terms: every document touch and system recommendation is chained into a cryptographic log. If anyone alters a past entry, the chain breaks — giving examiners and investors a verifiable answer to "how do I know this log hasn't been tampered with?"
Lender buyers — see also Security & compliance. Platform teams — ClawQL open-source docs.
Ready to see it on your files?
We walk through your document types and a condition workflow on a live loan.