Tinkerberry Labs
AI automation for insurance

Faster quotes, cleaner claims, tighter compliance.

Submissions arrive as email attachments, claims triage is manual, and renewal season eats the team alive.

Brokers and MGAsClaims operationsUnderwriting teamsInsurtech operators

70%+

of submission data extracted automatically

hours to minutes

first-notice-of-loss triage

100%

of renewals contacted on time

8

documented automations for this sector

The automations

Where insurance teams lose hours, and what replaces it.

Each one is a system we have specified and built before.

01

Submission intake and data extraction

The manual process today
Broker submissions arrive as varied spreadsheets and PDFs, rekeyed by underwriting assistants.
What we build
Automatic ingestion, extraction into your schema, completeness checking and an auto-reply requesting missing information.
Typical impact
Underwriters see clean, comparable submissions on day one.
Email ingestionDocument AIPolicy admin system
02

First notice of loss triage

The manual process today
Claims are triaged in the order they arrive, not by severity.
What we build
Classification by severity, complexity and fraud signal, with routing to the right adjuster and an instant acknowledgement to the claimant.
Typical impact
Serious claims reach the right desk in minutes.
Intake channelsClassification modelsClaims system
03

Claims document review

The manual process today
Adjusters read repair estimates, medical reports and invoices line by line.
What we build
Extraction and cross-checking against policy limits and coverage, surfacing inconsistencies for adjuster judgement.
Typical impact
Review cycles shortened; leakage reduced.
Document AICoverage rulesAdjuster review UI
04

Renewal campaign automation

The manual process today
Renewals are worked from a spreadsheet and some clients are contacted late.
What we build
Automatic renewal pipeline with market comparison packs drafted per client and multi-channel outreach on a schedule.
Typical impact
Retention protected; brokers spend time on negotiation, not admin.
Policy dataDocument generationOutreach automation
05

Coverage question assistant

The manual process today
Staff read long wordings to answer routine coverage questions.
What we build
An assistant grounded in your policy wordings and endorsements that answers with clause-level citations.
Typical impact
Answers in seconds with the source attached.
Wording RAGCitation enforcementAccess control
06

Complaints and regulatory reporting

The manual process today
Complaint logging and root-cause coding are inconsistent.
What we build
Automatic detection of complaints across channels, structured logging, root-cause classification and regulatory report drafting.
Typical impact
Regulatory deadlines met with an evidenced trail.
Channel monitoringClassificationReporting templates
07

Fraud signal detection

The manual process today
Fraud is spotted only when an adjuster has a hunch.
What we build
Cross-claim pattern analysis over networks, documents and text, escalating scored cases to SIU with the reasoning attached.
Typical impact
Suspicious clusters surfaced that manual review would miss.
Graph analysisText signalsSIU workflow
08

Quote comparison packs

The manual process today
Producing a client-facing comparison of five markets is a manual formatting job.
What we build
Automatic normalisation of quotes into a like-for-like comparison with a plain-English summary of coverage differences.
Typical impact
Comparison packs produced in minutes, consistently branded.
Quote ingestionNormalisation logicDocument generation
Questions

What insurance teams ask us.

Every automated classification stores its inputs, score and reasoning, and human decisions stay attached to the record so you can evidence any outcome to a regulator.

Yes. We deploy into your cloud tenancy where required, including private model endpoints and no data leaving your region.

Audits are a fixed fee and are credited against a build. Single-workflow builds typically land in the low five figures, multi-workflow programmes higher, and ongoing running and support is a fixed monthly fee. You get the number before we start, not a rolling hourly bill.

A first pilot on your real data usually runs within two to four weeks of the kickoff call. Full deployment with integrations and training normally lands between weeks four and eight.

Your automation plan

Tell us what your insurance team keeps doing by hand.

Thirty minutes, no pitch deck. We map the process, tell you whether automation pays back, and give you a rough cost before you commit to anything.

You and the work

Two more short steps sharpen the answer. An engineer reads it either way and replies, usually within a business day.

Other sectors

Automations for adjacent industries.