Neural FinanceNeural Finance

Capabilities

What brokers and lenders actually use

Start with Criteria AI and Broker Copilot — then the applications and CDM/DSL foundation that make them reliable in production.

01 · Criteria AI

Criteria search that understands lender policy

Natural-language criteria search across lender policy — structured rules, RAG, and GraphRAG with pass/fail checks against the client profile.

  • Modes for structured criteria rules, RAG, and GraphRAG
  • Toggle lenders and ask about CCJs, age, LTV, or credit in plain language
  • Apply the client profile for pass/fail against selected policy sources
Criteria AI interface with lender toggles, search modes, and criteria chat

02 · AI Broker Copilot

Broker Copilot with human–AI collaboration

Case-aware assist for status, tasks, fact-find gaps, documents, and suitability letters — with HITL queues that split work between brokers and AI agents.

  • Case-aware chat for status, tasks, summaries, and suitability letters
  • Fact-find and document prompts that keep journeys moving
  • HITL task hubs split work between AI agents and human brokers
AI Broker Copilot with quick actions and human-in-the-loop navigation

03 · Mortgage applications

Applications built around the model

End-to-end broker and lender apps: AIP → FMA, sourcing, KYC, submissions, and audit-ready case trails.

  • Broker CRM and case workspaces wired to the CDM
  • AIP → FMA promotion as a state transition, not a new record
  • KYC, sourcing, and lender submission in one trail

Mortgage applications

Built into the implementation

Delivered as working software in your mortgage stack — not a standalone bolt-on.

04 · Canonical data model

One schema for every mortgage journey

A FIX-inspired mortgage CDM — universal core, product archetypes, and governed lender extensions in one schema.

  • Universal Core fields present on every application
  • Residential, BTL, specialist, and bridging archetypes
  • Governed lender namespaces without shadowing core fields

Canonical data model

Built into the implementation

Delivered as working software in your mortgage stack — not a standalone bolt-on.

05 · DSL rule engine

Declarative rules credit teams can own

Declarative eligibility, affordability, and lender overlays evaluated against the live application object.

  • Eligibility, affordability, and stage rules as first-class assets
  • Lender overlays in their own namespaces
  • Evaluate against the live CDM object with an audit log

DSL rule engine

Built into the implementation

Delivered as working software in your mortgage stack — not a standalone bolt-on.

Foundation

Three-layer CDM & DSL

Universal core, product archetypes, lender extensions, and a rule engine that evaluates against the live application — the spine under Criteria AI and Copilot.

L1Universal Core
applicationIdapplicants[]loanproperty
L2Product archetypes
residential.*btl.*bridging.*
L3Lender extensions
halifax.*nationwide.*barclays.*
DSL rule engine

RULE MaxLoanToValue · APPLIES_TO UMC · LTV MUST NOT EXCEED archetype max

Human + AI

How brokers and agents collaborate

Criteria AI and Broker Copilot accelerate policy search and case operations. HITL task queues make the split explicit — agents propose and prepare; brokers review, decide, and remain accountable.

AI agents

  • Search criteria rules and policy documents
  • Summarise cases and flag open tasks
  • Draft suitability letters and document requests

Human brokers

  • Approve or override agent suggestions
  • Own advice and client recommendations
  • Clear HITL tasks before submission or commitment

Want Criteria AI and Copilot on your pipeline?

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