AI automation for the insurance admin that buries your team in paper

Insurance is a document business, done mostly by hand

Look at where the hours go in a brokerage or an insurer's back office and it is almost all document handling. A first notice of loss arrives by email, phone, or portal, and someone reads it, extracts the details, and keys them into the claims system. An application comes in and gets checked field by field against supporting documents. A renewal approaches and a broker gathers the current details, re-quotes, and chases the client for a decision before cover lapses. None of this is judgement about risk. It is administration, high volume, rule-based, and slow, and it is where service levels slip and clients get frustrated.

The instinct is to hire more processors, which adds cost and still leaves the work manual and error-prone. The real issue is that a handful of high-frequency jobs, claims intake, document processing, renewal preparation, follow the same rules every time and still get done by hand. That is the shape of work a machine handles best: high volume, clear rules, a real cost when something is mis-keyed or missed, a delayed claim, a lapsed renewal, a data-entry error that surfaces months later. We build and run those automations so your people spend time advising clients and handling the judgement calls, not typing forms.

Claims intake and document processing, done automatically

Claims intake is usually the fastest win. We build a pipeline that captures a first notice of loss however it arrives, email, phone, form, or portal, and an LLM reads the message and any attachments, extracts the structured details (policy number, claimant, date, description, amounts), validates them against your rules, and opens a clean claim record in your system with the documents filed and classified. The claimant gets an immediate acknowledgement and a clear next step instead of silence, and a handler starts from an organised file rather than a raw inbox. Anything the machine is unsure about routes to a human queue rather than being pushed through wrong.

The same document engine handles the wider back office. Applications and supporting documents are read, cross-checked for completeness, and the mismatches flagged for a person; policy documents are checked against the application; and structured data is written back to your policy or claims system with the original always kept for audit. The plumbing follows the job: simple app-to-app moves run on Make or Zapier, anything with branching or real document handling runs on n8n, which we self-host in the EU so personal and financial data never leaves an environment you control. Where your policy administration or CRM system exposes an API, we integrate directly; where it does not, we bridge with custom code. Nothing gets ripped out and replaced.

• First-notice-of-loss capture from email, phone, form, or portal, read and opened as a clean claim record automatically
• Document extraction and classification with structured write-back, original kept for audit
• Completeness checks on applications and supporting documents, with mismatches flagged for a person
• Immediate acknowledgement and clear next steps to claimants and applicants, instead of silence
• Low-confidence cases routed to a human queue, never silently filed or decided

Renewals that never lapse, and human judgement kept human

Renewals are pure lost revenue when they slip. We automate the tracking and the preparation: the machine watches for renewals coming due, gathers the current policy details, prepares the renewal pack, and starts a timed reminder sequence to the client well before cover lapses, escalating to a broker when a human conversation is needed. What used to be a broker manually working a renewal list becomes a managed pipeline where nothing falls through the gaps, and the broker's time goes to the conversations that actually retain clients and place the right cover.

The line we never cross: the machine handles the admin, a qualified person handles the risk. We do not automate underwriting, pricing, a coverage determination, or a claims decision, and we do not build systems that decide anything about a person's cover or payout. The AI reads, extracts, prepares, and reminds; a broker or handler reviews and owns every decision. This human-in-the-loop pattern is not a limitation bolted on afterwards; it is how the system stays compliant and how your firm stays responsible for the advice and the decisions it gives clients. Regulated decisions stay with regulated people.

Compliance, ownership, and when not to automate

Insurance data is personal and financial, and the sector is regulated, so this is built for compliance from the first line. We keep personal and financial data inside an environment you control: n8n self-hosted in the EU or on your own infrastructure, no client data sitting in a third-party tool's logs, and a clean data-processing agreement under GDPR. Every run is logged and auditable, so you can always show what was processed, extracted, and escalated, and by what rule, which matters when a regulator or an internal audit asks. You own the workflows, logic, and integrations outright, documented, with no lock-in.

We are also honest about where automation does not belong. Underwriting, pricing, coverage determinations, and claims decisions stay with your qualified people, full stop. A workflow that runs a handful of times a month rarely justifies a machine, and one whose rules shift with every regulatory change costs more to maintain than to do by hand. We tie our fee to the automation running in production and doing the job, and we scope to the numbers first: how many claims, how many documents, how many renewals, what a mis-key or a lapse costs. If it will not clear the bar, we tell you before we build, not after.