Northgale is an Explainable AI decision layer any product can embed. Aegis is the same engine shipped as a finished product for insurance agents — the live proof that explainable AI works in the real world before you build on it.
Drop an API between your AI models and your users. Every recommendation comes back as a decision card — a plain-language rationale, the evidence trail behind it, a confidence score, risk flags, and a recommended next action. No black boxes.
Send a model output, get back a structured, human-readable card your product can render anywhere.
Every card cites the source notes, records, transcripts, or documents behind the recommendation so users can verify before they act.
A 0–100% confidence score plus an explicit list of what could be wrong — surfaced up front, not buried.
Log the full reasoning trail and export it for reviews, approvals, and governance.
Prioritize Northstar Logistics for enterprise outreach this week.
Ranked first because three buying signals overlap: budget timing, repeated security-review language, and an executive mandate around AI governance.
Well-documented: recent coverage review logged, signed proposal on file, and two follow-ups closed. Strong E&O posture.
A book-of-business tool for independent insurance agents — the live proof of the Northgale platform. It scores how well each client file is documented for Errors & Omissions defense and writes plain-English coverage explanations, every card backed by the same evidence-and-confidence engine.
Every client, policy, and renewal date in one timeline that stays current on its own.
A 0–100% score grading how defensible each file is, with a specific list of what is missing and the exact next action to close the gap.
Ask whether your book is growing, what renewals are coming, and — reading your own notes — which clients look ready for a new or additional policy. Every answer cites the note it came from.
Connect Google or Microsoft and appointments, calls, and renewal dates flow into each client timeline, matched automatically by attendee email.