Most AI in insurance is a demo. It looks cool on the slide, it works on the sample, and then it meets a real insurance task and flags the header as a defect.
Ours is in production. Our AI QA Agent went live in June 2026 and runs on top of your loss control forms in LC360, built on years of loss control inspection & system integration experience, and is configurable to other client platforms. Our AI Pre-Call Agent went live in July 2026 and is making confirmation calls today. We built both, we run both, and we built them for one industry, which is the #1 reason they already work.
AI PRODUCTS IN PRODUCTION
AI QA Agent LIVE
AI PRE-CALL AGENT LIVE
Loss Control-FOCUSED
A general-purpose quality tool reads a loss control report and sees text. It checks spelling, grammar, and structure. It has no idea that a Class 3 building with no egress recommendation is a finding, or that a recommendation written but never threaded to its follow-up is a compliance gap, or that a narrative edit which changed the meaning of an inspector's observation is the single most expensive error in the workflow.
It does not know because nobody taught it. The rules inside a generic tool came from generic text.
The rules inside ours came from our loss control QA checklists — and those checklists came from the two-sided scorecard we have run manually for years across live loss control programs. Program-level trends on one side, individual inspector error patterns on the other. Every error classified: a true error goes to accountability, something genuinely new goes into the checklist. Learn, apply, maintain. Do that long enough across enough real inspection reports and you end up with a document that describes exactly how loss control quality work fails in practice. That document is the training data. That is what we encoded. The moat was never the model — anyone can rent a model. The moat is the decade of tracked loss control error patterns that told the model where to look, and the QA professionals who reviewed and validated the output, including client-side review.
Loss control sits inside underwriting, one step in the policy lifecycle. Plenty of AI tools handle other insurance functions well. We do not compete with them. We built for the segment we have run for a decade: pre-inspection confirmation through post-inspection QA.
The same capability that built our AI QA Agent is available as a service. Model development support, data preparation and labeling, training and optimization, and predictive insight integration, delivered by a team that has actually shipped a domain-specific model into production against live Loss Control workflows, not one that has read about them.
Automation only pays when it is pointed at the right process. We document the workflow first, find the steps that should not exist, eliminate those, and automate what remains. Automating a broken process just produces broken output faster, whether that's a loss control workflow or broader operational administration workflows across the business..
Insurance marketing run by people who understand insurance distribution, including AEO, GEO, and LLMO, because a growing share of prospects now ask a language model before they ask a search engine.
Our AI is in production, not in a roadmap. AI QA Agent live June 2026, AI Pre-Call Agent live July 2026
The rules came from real error data on real Loss Control reports, not from generic validation logic.
Reviewed and validated by QA professionals, including client-side review.
Loss control native. In insurance business process outsourcing, offshore competitors staff generalist, multi-vertical teams and train them on your work.
SOC 2 Type 2 certified and ISO 27001 certified, with annual third-party penetration testing.
The use of automation and AI to eliminate repetitive manual steps in a workflow, improve accuracy, and increase throughput. In insurance operations it applies to order entry, document handling, quality review, and communication workflows.
In production. Back Office Operations Solutions Team's AI QA Agent went live in June 2026, and Back Office Operations Solutions Team's AI pre-call agent went live in July 2026. Both were built in-house, and both run against live Loss Control workflows today.
It sits on top of LC360 — and is configurable to other client systems — and checks work against a rule set encoding how loss control quality work actually fails. It flags domain findings, not spelling errors.
From Back Office Operations Solutions Team's QA checklists, built over years from the manual two-sided scorecard Back Office Operations Solutions Team runs across live programs: program-level trends plus individual error patterns. That accumulated record is the training data.
Yes. It has been reviewed and validated by QA professionals, including client-side review.
Because a generic tool sees text. It cannot know that a Class 3 building with no egress recommendation is a finding, or that a narrative edit changing an inspector’s meaning is the most expensive error in the workflow. Nobody taught it. The rules inside a generic tool came from generic text.
A voice agent making pre-inspection confirmation calls on behalf of carriers. It went into production in July 2026 and is actively making calls, with script refinement ongoing as it runs against live volume.
Yes. AI and machine learning model training is a service line — model development support, data preparation and labeling, training and optimization, and predictive insight integration. It is the same capability that produced Back Office Operations Solutions Team AI QA Agent.
It will, if you automate before you document. Back Office Operations Solutions Team maps the workflow first, eliminates the steps that should not exist, then automates what remains. That order matters more than the tooling.
Administrative task management, calendar and meeting coordination, email and communication support, and document and workflow assistance — staffed by insurance-literate team members.
Answer Engine Optimization, Generative Engine Optimization, and Large Language Model Optimization — optimizing to be cited by AI answer surfaces, not just ranked by search engines. A growing share of insurance buyers ask a model before they ask Google.
Under the same controls as every other engagement: SOC 2 Type 2 certified, ISO 27001 certified, annual third-party penetration testing, biometric access control, and a controlled, monitored environment.
Generic AI can demonstrate what’s possible. Our production-tested AI is built around how loss control work actually gets reviewed, processed, and resolved. See how our AI QA Agent and intelligent automation can work against your own Loss Control workflows and reports.
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