PURPOSE-BUILT FOR COMMERCIAL LINES
Agentic Underwriting AI for Mid-Size P&C Carriers
Write more business. Sharpen renewals. Standardize every decision, without adding additional headcount.
Nallas deploys AI use cases built specifically for commercial lines underwriting teams. Private cloud. Your guidelines. Your data. Live in your environment in 6-8 weeks.
Underwriting Specific AI Use Cases. Built for Lean Underwriting Teams.
The Submission Gap: 60% of submissions go unreviewed. Good risks walk out the door with the broker.
The Leakage Problem: Decisions vary 15-25% across underwriters on identical risks. That inconsistency hits your loss ratio.
The Manual Burden: Loss run reviews consume 40% of an underwriter’s week, most of it manual data entry.
From
Manual Submission Triage
To
Agentic Submission Scoring
From
15 - 25 % Decision Variation
To
Standardized Guideline Enforcement
From
4 - Hour Manual Loss Run Extraction
To
Instant Structure from Summaries
Targeted AI agents. Each POC-ready in 6-8 weeks.
AGENTIC USE CASES & CAPABILITIES
Write 3-5x more business with the same underwriting team.
Brokers don't wait. When a submission sits unanswered, they move on and the good risks go with them. Our triage agent reads every incoming submission, matches it against your appetite and class guidelines, scores it, routes it to the right underwriter, and drafts a preliminary response, all in minutes. Your team reviews decisions, not inboxes. Built on our partner Arivonix's agentic AI platform with private cloud deployment, so submission data never leaves your environment.
3 weeks → 3 hours
One carrier's submission processing time after deploying agentic triage.
Every underwriter gives the right answer, every time.
Ask two underwriters the same coverage question, get two different answers. That 15-25% decision variation is invisible until it shows up in your loss ratio. Our Guidelines AI makes your appetite documents and underwriting rules instantly queryable in plain language, the underwriter gets the answer with the specific guideline cited, in seconds. Consistent, defensible, and audit-ready. No senior underwriter interrupted. No 30-minute search through PDF binders.
76%
Of insurance staff spend 30%+ of their workday searching for information rather than acting on it.
Price renewals with data, not gut feel.
A single commercial renewal with multiple loss run PDFs takes 2-4 hours of manual extraction, cross-referencing, and spreadsheet work. Multiply that across your renewal book and the math doesn't work. Our Loss Run Intelligence Agent ingests PDFs in any format, normalizes loss history, calculates frequency and severity trends, flags anomalies, and delivers a structured pricing summary, ready in minutes. Underwriters apply judgment. They don't transcribe data. Built on Databricks for processing scale, with full auditability on every extracted figure.
40%
Estimated share of underwriter time consumed by manual loss run processing, most of which can be automated.
Your AI is only as good as the data feeding it.
All three underwriting AI use cases depend on clean, governed insurance data. As a Databricks Certified Partner, Nallas builds cloud-native data platforms that unify your submission, policy, claims, and loss data from legacy systems and external sources—AI/ML-ready from day one. We integrate with your existing policy admin, claims, and rating systems so the platform fits your environment, not the other way around.
Dense insurance documents. Instant, structured answers.
Policies, endorsements, coverage forms, reinsurance treaties, underwriters and ops teams spend hours cross-referencing these manually. Our GenAI document intelligence layer enables precise clause extraction and comparison, intelligent search across large document sets, and plain-language Q&A over your entire document library. Coverage question? Answered in seconds. Policy form comparison? Done in minutes, not hours.
VALUE PROPOSITIONS & DIFFERENTIATORS
Designed for carriers with lean underwriting teams and 50M-500M in DWP, not scaled-down enterprise tools built for carriers ten times your size.
Every use case ties to a measurable underwriting KPI—submissions reviewed, decision consistency rate, loss run processing time—not a vague technology roadmap.
Most vendors offer AI or data engineering. Nallas brings both, Arivonix's agentic AI and Databricks' data platform, integrated by a team with commercial lines depth.
One use case. One team. Six weeks. Prove it works in your environment, then scale. You de-risk the investment at every step.
Your underwriting data stays in your environment, fully isolated from public AI infrastructure, with no data governance surprises.
Ready
Plugs into your existing policy admin—underwriters adopt it in the tools they already use every day.
OUR SYSTEMATIC APPROACH
We start by mapping your submission intake, renewal process, loss run handling, and guideline management, identifying precisely where underwriters lose time and decisions lose consistency.
We identify which of the three use cases delivers the fastest measurable impact for your team and define success metrics, data inputs, and integration points before writing a line of code.
We deploy the prioritized use case in your environment using your actual data and guidelines. You see it work and measure the results, before any full-scale commitment.
Proven POC scaled into a production-ready system, integrated with your policy admin, claims, and workflow platforms, with full auditability and compliance controls in place.
WHY NALLAS
Domain Knowledge
Submission triage, renewal pricing, decision consistency, appetite management—built from real commercial lines underwriting workflows, not generic AI theory applied to insurance.
Already Assembled
Arivonix (agentic AI, private cloud), Databricks (data platform, Nallas is Certified Partner), and any other custom partner of your choice, integrated and ready, not assembled from scratch per engagement.
Results Before You Commit.
Every engagement starts with a focused proof of concept on one use case, using your data, with defined success metrics, you see it work before making any full-scale decision.
Leaves Your Environment.
All AI runs in a private cloud via Arivonix, submission data, loss runs, and underwriting decisions are fully isolated from public AI infrastructure. Compliance-ready by design.
CORE COMMITMENTS
We’ve built these use cases from real underwriting workflows, we understand the day-to-day, not just the AI that serves it.
Our partner stack: Arivonix &Databricks, are already integrated and aligned. You get a solution, not a vendor coordination project.
Guideline cited. Loss data sourced. Score rationale visible. No black box, your underwriters stay in control of every decision.
We never ask for a full program commitment before proving value. One use case, one team, six weeks, then we earn the next one.
Submissions reviewed per underwriter per week. Decision consistency rate. Loss run processing time. We’re accountable to your numbers, not ours.
Nallas is building a dedicated insurance AI practice for the long term, structured to grow with your underwriting team as the technology evolves.
Resources
Explore our Resources for insights, tools, and innovation that drive digital transformation insurance data modernization. From blogs and case studies to white papers and hackathons, find everything you need to stay ahead. Learn, build, and grow with Nallas.
Start with a Conversation
Whether you’re exploring insurance data modernization, data modernization solutions, or AI adoption; we help insurers find the right starting point.
Talk to our Insurance Solutions Team.
