AI FOR EDUCATION & EDTECH

Custom AI/ML solutions for education & edtech industry

Custom AI and ML for K-12 districts, higher-ed institutions, and edtech platforms. Personalized learning, enrollment intelligence, content moderation, and outcomes analytics — built for FERPA and accreditation.
25–35%

Mispricing reduction in cyber lines via our loss-frequency models

5 → 1 day

Submission-to-quote cycle time after triage LLM deployment

70%

Reduction in claim-handler triage time on ransomware claims

Achieve immediate, organization-wide results

Six measurable outcomes across underwriting, claims, and actuarial functions — deployed in months, not years.

Faster Quote Cycles

Submission triage LLM cuts submission-to-quote from 5 days to 1 — with the same underwriting rigor.

Defensible Loss Models

Cyber, climate, and parametric loss-cost models that hold up at regulator review and treaty negotiation.

Automated Document AI

ACORD form extraction, title docs, loss-mit packets — boarded in seconds, audited end-to-end.

Fraud Detection

Wire-fraud detection on email threads + claim anomaly scoring — defending the bottom line.

Damage Assessment

Computer-vision claims triage from photos to severity estimate — in seconds, not hours.

Risk Engineering Agent

OSINT control-posture scoring + risk-engineering recommendations — differentiator vs commodity carriers.

Capabilities across the insurance value chain

Underwriting

Claims

Actuarial & Loss Modeling

Operations

From the playbook

How a mid-size cyber MGA cut submission cycle time 80%

A cyber-focused MGA writing $40M in annual premium was losing brokers to faster carriers. Submissions were taking 4–6 days to quote because every submission went through manual control-evidence triage. We deployed a submission triage LLM + OSINT control-posture scorer that pre-scored every inbound submission against the carrier’s appetite + control attestations. Underwriters now see a pre-scored submission in the inbox with appetite fit, missing-info flags, and a triaged risk profile — they confirm or override in 30 minutes. Submission-to-quote cycle time dropped from 5 days to under 1. Bind rate up 14%, broker satisfaction scores up 32%.

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Speak with an insurance AI expert

A 45-minute scoping call. We’ll come prepared with your appetite, your loss-cost benchmarks, and a directional read on which models move the needle on your line of business.

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    Frequently asked questions

    How quickly can a first model be in production?
    Yes. Our deepest experience is in P&C (cyber, auto, commercial) but we've shipped models in life, health, and parametric as well. Carrier-agnostic and reinsurance-aware.
    For well-scoped projects with clean data access (ACORD extraction, submission triage), 8–12 weeks. For cat/accumulation models requiring custom data acquisition, 14–20 weeks. We always start with a 45-minute call to scope realistically.
    Every model ships with a full MRM package: documentation, sensitivity tests, backtesting against holdout periods, sign-off-ready validation pack. We've shipped models that have passed CCAR/DFAST-style scrutiny and state regulator review.
    No. SaaS is great for screening and at-scale commodity workflows. We build custom models per-deal where the analytical edge matters — cyber pricing, niche cat modeling, claim-segment automation. Different problem, different tool.

    Explore insurance-specific niches & solutions

    Ready to talk insurance AI?

    Start with a 45-minute strategy session. We come prepared with a directional read on your line of business and a scoped proposal.