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The leading platform for reinsurers/insurers/MGAs who compete on speed, accuracy, and operational excellence.
- placing@broker.exampleSOV · Acme Warehouse
- london@broker.exampleSlip · Q3 renewal
- claims@broker.exampleLoss run · 2019-2021
| Field | Value | Conf. | Source |
|---|---|---|---|
| Limit | $25,000,000 | 94% | p.14 |
| TIV | $142,800,000 | 91% | Sheet: SOV!C12 |
| Occupancy | Warehouse | 88% | p.3 |
| Deductible | $250,000 | 96% | p.14 |
- SOV occupancy uncoded (3 locations)
- Loss run years 2019-2021 missing
- Target premium not stated
OAuth · read-only scope · full audit log · revoke anytime
Plugs into where you already work
Any internal system can become a source or a destination through open MCP connectors, with no rip-and-replace and no data exports.
Every connector is org-scoped, permissioned per team, and every read is written to the audit trail.
Every field shows its work.
Each extracted value carries its source document, page or cell, a confidence score, and any conflicting values from other documents. Your underwriters review evidence. They don't re-key data.
Specialised Agent Catalog
Composable AI agents designed for specific reinsurance/insurance workflows. Deploy individually or combine for end-to-end automation.
Submission Agent
Job: turn a broker inbox of slips, SOVs, and loss runs into a traced facultative pack with a chase list for missing pages.
Bordereaux Agent
Job: turn messy cedent premium, claims, and commission bordereaux into rows that map to treaty terms, with gaps instead of guessed totals.
Treaty Agent
Job: pull attachment, limits, exclusions, and reinstatement language from treaty PDFs so accountants are not re-typing clauses.
Loss Run Agent
Job: normalize loss runs from mixed PDFs and spreadsheets into a dated history an underwriter can trust, with missing years listed as gaps.
Compliance Agent
Job: extract filing-relevant fields from the documents you already have, then list what is still missing for Lloyd's, Bermuda, or Solvency II packs.
Pricing Agent
Job: assemble pricing inputs (exposure, experience, cited attachment) so a human can set technical price. The agent does not silently bind a layer.
Plus 19 specialist agents across exposure, recovery, ILS and capital →
Underwriting Agent
Job: compare a traced pack to stated guidelines and list what is in, out, or missing. It does not silently bind a layer.
Contract Agent
Job: pull named insured, period, limits, deductibles, and endorsements from wording PDFs with a source span, or list the gap.
Schedule Agent
Job: turn an SOV into a summable location list with as-at date, or flag rows that cannot be totalled.
Actuarial Agent
Job: extract cited assumptions and figures from actuarial PDFs so pricing conversations use the same numbers as the report.
Triage Agent
Job: classify an inbound pack by class and completeness, then route it. Incomplete files stay on the chase list, not in a fake-complete queue.
Exposure Agent
Job: aggregate traced locations and limits into an exposure view, and list schedules that still have no as-at date.
Retention Agent
Job: assemble retention and cession inputs from cited wordings and bordereaux so a human can choose structure. It does not pick the programme.
Capital Agent
Job: gather filing-relevant fields that already exist in the pack and list what is still missing for a capital conversation.
Accumulation Agent
Job: roll traced locations into peril accumulations and surface schedules that cannot be geocoded or summed.
Retrocession Agent
Job: extract retrocession structure, attachment, and reporting fields from the contracts you already have, with gaps instead of guessed layers.
Quote Agent
Job: draft a quote memo from traced pack fields and list what still blocks a number. It does not invent a limit to look complete.
Claims Agent
Job: map loss notices and claims bordereaux to treaty terms, then list breaks, duplicates, and missing as-at dates.
Market Agent
Job: keep market, broker, and placement notes next to the pack so a desk is not pricing from a covering email.
Portfolio Agent
Job: show how traced in-force limits sit against stated appetite, and list policies whose schedules still do not sum.
Renewal Agent
Job: compare expiring wording and bordereaux year-cuts to the renewal pack, and list fields that changed without a span.
Performance Agent
Job: compute ratios from premium and claims files that already reconcile, and refuse a combined ratio when the year-cut is still a gap.
Clash Agent
Job: find where the same event language could hit more than one treaty in the pack, and cite the clauses rather than infer them.
Commutation Agent
Job: extract outstanding, paid, and commutation language from the files you have, then list missing reserve as-at dates.
Sidecar Agent
Job: pull sidecar reporting fields from agreements and bordereaux, and list collateral or performance items still without a source.
ILS Agent
Job: extract trigger, term, and reporting language from ILS documents, and leave unsourced return figures as gaps.
The 4-Layer Insurance Intelligence Stack
Most AI tools in insurance operate at a single layer: extracting documents or automating a task. Reinsured.AI is architected across all four layers, with the Context Cloud as the connective intelligence that no point-solution vendor can replicate.
Explore the full architectureOrganisational Sovereign AI for Insurance
Reinsure-8B is the world's first purpose-built small language model for the reinsurance industry, fine-tuned from Llama 3.1, trained on reinsurance workflows, treaty structures, and market language. Your organisation can run it fully sovereign, or consume it via a simple inference API.
Unlike generic LLMs applied to insurance, Reinsure-8B speaks your language out of the box. No prompt engineering, no hallucinated policy terms, no data leaving your perimeter.
Explore the modelTrust Architecture
Built for institutional reinsurance environments. Security, compliance, and data sovereignty are non-negotiable.
automated tests on every release
real-world document sets in our regression corpus
records benchmarked
of extractions carry field-level provenance
Renewal season, measured in hours.
Quick Questions
Essential answers about AI automation in reinsurance operations.
What is Reinsured.AI?
Reinsured.AI provides specialized AI agents for global reinsurance operations. Our production-ready agents automate document processing, underwriting, pricing, compliance, and portfolio management, eliminating the 40% manual data entry waste that plagues reinsurance teams.
How quickly can we implement?
Standard integrations go live in 48 hours. Complex custom workflows may take 1-2 weeks. Unlike legacy system replacements, our API-first architecture layers on top of existing systems, so there's no rip-and-replace required.
What's the typical ROI timeline?
Most deployments show positive ROI within 3-6 months. Clients report 40% time savings on manual tasks, $7-9M annual operational savings, and 60% faster submission processing. The Bordereaux Agent alone saved one Zurich reinsurer $8.2M annually.
Is our data secure?
Yes. Your treaty data never trains our models. We're SOC 2 Type II and ISO 27001 certified with data encryption at rest and in transit. Support for data residency requirements (US, EU, APAC) and on-premise deployment for Lloyd's market participants.
Do we need to replace existing systems?
No. Our API-first architecture integrates via REST APIs and webhooks with existing policy admin, accounting, and document management systems. We layer on top of your current infrastructure: no rip-and-replace required.
Can agents handle both insurance and reinsurance?
Yes. While we specialize in reinsurance complexity (bordereaux, treaty structures, facultative slips), our agents also serve primary insurers and MGAs. We support property CAT, casualty, specialty lines, life & health, and ILS structures.