Industry · Insurance
For claims, underwriting, and policy operations.
We build the software and AI that runs inside a carrier, MGA, or broker — claims automation, underwriting support, policy administration, document intake, and fraud detection — grounded in your own policy and claims data, wired to the core you already run.
Every automated decision explainable and auditable, with a human in the loop where it counts. We don't set your rates or replace your core.
On top of your core, the decision stays yours
The problem
Why so much insurance work is still manual when the data is already there.
Because the work is buried in documents and locked in core systems that were never built to talk to anything. A claim arrives as a PDF, an email, photos, and an adjuster's notes; a submission lands as a spreadsheet and a broker's narrative.
The data a carrier needs to triage, price, and decide is present — it's just trapped in unstructured form, re-keyed by hand, and routed by tribal knowledge. So cycle times stretch, leakage creeps in, and the expensive people spend their day on data assembly instead of judgment.
The gap isn't a new core or more headcount — it's the software layer that reads what the documents already say, scores and routes the work, and puts a recommendation in front of the right person while the decision still belongs to them.
estimated annual cost of insurance fraud to the U.S., across all lines — the scale a fraud-detection and SIU-support layer is built to attack.
The recovery is real — but so is the cost of accusing the honest, which is why a person owns every call.
What we build
Where insurance software earns its keep — and what each use case delivers.
High-leverage applications that sit on top of your existing policy and claims systems. Every one is built so a person owns the decision the software recommends.
Claims processing automation
Ingests the FNOL, classifies and routes it, extracts facts from documents and photos, flags simple claims for fast settlement and complex ones to an adjuster.
Benefit — shorter cycle times and lower leakage, adjusters freed for the cases that need judgment.
Example: a clean auto glass claim is triaged to settlement in minutes — while a disputed total-loss claim goes to a senior adjuster with the file already assembled.
Underwriting support & submission triage
Reads submissions, pulls third-party and internal data, surfaces risk signals, and gives the underwriter a prioritized, pre-assembled view — without setting price.
Benefit — faster quote turnaround, more submissions worked per underwriter.
Example: a commercial submission that took days arrives pre-summarized with data gaps flagged, so the underwriter quotes or declines same-day — rating and final call stay with them.
Policy administration & self-service
Workflows, portals, and integrations for issuance, endorsements, renewals, and servicing — so what took a chain of emails happens in a guided flow wired to your core.
Benefit — lower service cost and faster turnaround on routine policy work.
Example: a policyholder requests a coverage change and a self-service flow updates the core system directly, instead of waiting on a back-office queue.
Document & data intake (IDP)
Turns the PDFs, ACORD forms, emails, and images that flood every process into structured, validated data your systems can use.
Benefit — the re-keying disappears and downstream automation finally has clean inputs.
Example: a loss-run report or ACORD certificate is read and validated on arrival — fields extracted, exceptions flagged — instead of a clerk typing it in field by field.
Fraud detection & SIU support
Scores claims and applications for fraud, surfaces suspicious patterns and network links, and routes the right cases to the SIU with evidence assembled.
Benefit — more genuinely suspicious claims caught earlier, fewer false accusations of honest policyholders.
Example: a claim fitting a staged-accident pattern is flagged for SIU review before payment, while clean claims flow through untouched — so investigators spend time where recovery is.
Customer & broker servicing assistants
Answers policy, claim-status, and coverage questions for policyholders and brokers from your approved sources, escalating anything it's unsure of.
Benefit — instant answers on routine questions and lower call volume, without unapproved or invented answers.
Example: a broker checking a submission's status, or a policyholder asking their deductible, gets a grounded, sourced answer at any hour — escalating the moment confidence drops.
The measured impact
What this software does to insurance work.
Independent, third-party findings on what AI and automation do to insurance operations — cited as industry evidence, not Silicon Prime client results.
Annual US insurance fraud
across all lines — the scale a fraud-detection and SIU-support layer attacks.
Revenue gen-AI could add
to the industry, concentrated in marketing, customer ops, and software engineering.
Quote turnaround
compressing from weeks to days — in some commercial lines from days to hours — as AI takes over data assembly.
Cut from liability assessment
at Aviva (80+ AI models) — plus +30% routing accuracy, −65% complaints, £60M+ saved. Aviva's result, not ours.
Every automated recommendation carries an explanation, an audit trail, and a human who decides.
Our software assembles data, surfaces risk signals, scores and routes work, and recommends — but the rating and the final decision stay with your underwriters, adjusters, and actuaries. Human-in-the-loop review is designed in wherever a wrong call costs a claim or a customer. We build to be auditable; regulatory sign-off stays with your compliance function, and we build the evidence trail that makes their job possible.
The scope
What insurance software development covers.
The operations and intelligence layer — what reads, scores, routes, and recommends on top of your core. We integrate with your policy-admin, claims, and rating systems; we don't replace the core or set actuarial rates.
Claims automation & workflow
Intake, triage, routing, and straight-through-settlement workflows around your claims system — including the ML models that classify and prioritize claims, validated against your history so adjusters trust the routing.
Underwriting support & risk models
Submission ingestion, third-party data enrichment, and risk-signal surfacing that give underwriters a pre-assembled view — on your own data. We support the decision; we don't set the price.
Policy administration & servicing apps
Portals, guided workflows, and integrations for issuance, endorsements, renewals, certificates, and self-service — wired into your core PAS, not replacing it, plus modernization of the brittle legacy pieces.
Document & data intake (IDP)
Pipelines that turn PDFs, ACORD forms, emails, and images into structured, validated data — with the validation that makes the output trustworthy, exceptions flagged for a human.
Fraud detection & SIU tooling
Fraud-scoring models and network analysis tuned against your history to balance catch rate against false positives, routing flagged cases to your SIU with evidence assembled for a person to judge — never auto-denial.
Servicing assistants & integration
Grounded customer- and broker-facing assistants on your approved sources, plus the governed integration layer that ties every application back to your core — auditable end to end.
What you get — all assigned to you under full work-for-hire IP transfer
How it runs
One accountable lead, fixed scope, no handoffs.
Tuned for a regulated, auditable environment. Most engagements reach production in 4–8 weeks, full IP assignment signed at kickoff.
Discover
Scope one process and the metric it targets — claim cycle time, quote turnaround, fraud-catch rate, service cost — and confirm the data and the human-review points it needs.
Output: a ranked plan & the metric we'll be judged on
Connect
Integrate your policy-admin, claims, rating, and document sources through governed, permissioned interfaces — with the audit trail built in from the start.
Output: a trusted, auditable data foundation
Build
Develop the application and, where it applies, train and validate the model against your historical outcomes — with explainability and human-review checkpoints designed in, not bolted on.
Output: a working system tested on your real data
Deploy & enable
Pilot on one process, prove the metric moves with the controls holding, then scale — your team trained to operate, retrain, and audit it.
Output: a production system & a team that owns it
The track record
No carrier client yet — but the transaction-integrity engineering a regulated system demands.
We'll be straight: our named case studies are not insurance carriers. What carries over is the production-reliability and transaction-integrity engineering a regulated insurance system demands — and the human-in-the-loop discipline that is our founding charter.
Our deepest proof is in restaurants (BJ's, a 200+ location operation held at zero critical defects for four years) and a financial-transaction marketplace (YardClub, $120M+ processed, acquired by Caterpillar). For a first insurance engagement we scope a contained pilot on one process — claims triage, document intake, an SIU model — to prove the value first.
Responsible AI is the founding charter, not a feature. Explainability, audit trails, and a human owning every consequential decision are how we build — which is exactly what a regulated carrier needs. We build the evidence trail; regulatory sign-off stays with your compliance function.
Silicon Prime is a Stanford-rooted Responsible AI lab, founded in 2011, run by founder Kelvin Tran — personally accountable for every engagement, in writing.
YardClub
A financial-transaction marketplace built end to end — listings, payments, reconciliation. $120M+ processed; acquired by Caterpillar in 2017. The transaction-integrity and money-movement engineering a regulated claims or payment system needs.
BJ's Restaurants
A 200+ location operation held at twice-a-week releases with zero critical defects across four years — the production-reliability engineering a regulated insurance system the carrier depends on has to clear.
Why build it with us.
We support the decision, never automate the accountability. Every recommendation is explainable and audited, with a human owning anything consequential — the only way an automated insurance decision survives a regulator or a dispute.
On top of your core, not a rip-and-replace. We integrate with the policy-admin, claims, and rating systems you run through governed interfaces — and tell you honestly when a legacy piece is worth modernizing instead.
Models investigators and underwriters trust. Fraud and triage models are tuned against your own historical outcomes — balancing catch rate against false positives — so the team relies on them instead of overriding them.
Founder-led, built to transfer. One accountable lead; the apps, models, and pipelines are assigned to you, your team trained to operate, retrain, and audit them.
Where this connects
An insurance build rarely stands alone.
It rests on the same engineering we bring to neighboring work.
Fintech & payments
For payments, lending, and real-time decisioning — the transaction-integrity engineering claims payouts share, on a different workflow.
Fintech software →Machine learning development
The fraud, triage, and risk models behind an insurance build — validated on your historical outcomes, explainable by design.
ML development →Conversational AI
Customer- and broker-servicing assistants grounded in your approved sources, escalating to a person the moment confidence drops.
Conversational AI →Questions buyers ask before they build.
Do you replace our policy-administration or claims core system?+
Do your models set premiums or make the final underwriting or claims decision?+
How should we evaluate an insurance software development partner?+
How do you handle fraud detection without falsely flagging honest policyholders?+
Do you have insurance clients we can reference?+
How do you handle our data, security, and compliance?+
Who owns the software and the models when we're done?+
How fast can we see something working, and what does it cost?+
Thirty minutes · No pitch deck
Ready to put the data to work while the decision stays yours?
Bring the process you want to attack — claims triage, submission intake, an SIU model, a servicing flow — and we'll tell you honestly whether your data supports it, what it takes to build auditably, and what it costs to run.