How We Work

From First Call to Live AI Underwriting — In Weeks

We make advanced AI easy to adopt. Our team handles the heavy lifting—data, modeling, integration, and training—so your underwriters get faster, clearer decisions without changing how they work.

Our Process

A Clear Path from Idea to Impact

Six guided steps. Minimal disruption. Results you can measure. We tailor each deployment to your policies, risk appetite, and workflow.

01

Discovery & Success Plan

We map your underwriting flow, data sources, and decision rules, then define the wins that matter to you.

  • Existing tools, bottlenecks, and manual checks
  • Success metrics: time-to-decision, approvals, risk
  • Security & compliance requirements
02

Data Ingestion & Cleaning

We connect bank statements, processors, CRM, and third-party data—normalize it, and remove noise.

  • Bank & processor connectors
  • PII handling and encryption at rest & in transit
  • Audit-ready data lineage
03

Model Design & Policy Alignment

Your risk policy becomes the blueprint. We build Explainable AI models that reflect how you underwrite.

  • Feature engineering for cash flow & risk
  • Transparent reason codes for every decision
  • Bias checks and fairness constraints
04

Workflow & System Integration

We fit into your stack—no big rebuild. Underwriters keep their tools; decisions get smarter.

  • APIs & webhooks to your CRM/LMS
  • Single sign‑on & role-based access
  • Sandbox + staged rollout
05

Training & Change Enablement

We enable your team with hands-on sessions, quick guides, and office-hours. Adoption is built in.

  • Playbooks for analysts & managers
  • Explainability-first decision screens
  • Dedicated Slack / email support
06

Optimization & Governance

We monitor results, tune models, and keep you compliant as data and markets evolve.

  • Performance dashboards & drift alerts
  • Versioning, approvals, and rollback
  • Quarterly reviews & roadmap
Speed to Value

Live in Weeks — Value in Days

Most teams see measurable gains within the first month. Here's a typical rollout:

Week 1
Discovery, data access, success plan
Weeks 2–3
Model build, policy codification, sandbox
Weeks 4–6
Pilot rollout, training, KPI dashboards
Security & Compliance

Enterprise-Grade Protection, Built In

Data is encrypted, access is controlled, and every decision is auditable. We design for your regulator, not just your roadmap.

Data Protection

Encryption & Access

PII is protected at rest and in transit. SSO, MFA, and roles keep sensitive data locked down.

Governance

Explainability & Audit Trails

Every output includes reason codes, version IDs, and exportable logs for internal and external audits.

Controls

Policy & Fairness

Bias checks, threshold reviews, and approval gates ensure decisions align with policy and fairness standards.

Ready to modernize your underwriting?

We'll tailor a live demo to your process and show exactly where AI accelerates decisions without adding risk.