insurance operations, prebuilt.

the AI-native Business Process Outsource (BPO) solution for (re)insurers. AI agents that already know what needs to get done.

from SOVs, to loss runs, and FNOL — pretrained on $400B+ of insurance transactions, powered by an Insurance Knowledge Graph and domain-specific language model (dsLM).

BPO throughput at AI economics, with the speed, accuracy, and context-awareness only insurance-native AI delivers.

See mea Operations in action

what is mea Operations.

mea Operations is an AI-native BPO solution for (re)insurers. Carriers, MGAs, and brokers use it as an alternative to labor-based BPO — running underwriting, claims, finance, and policy servicing end to end.

mea is in production with 30+ insurance customers across 20+ countries, processing $200B+ in annual transaction value.

different operating models to achieve BPO outcomes. only one already knows insurance.

mea Operations
traditional BPO labor model
operating model
insurance-native AI agents, prebuilt
people intensive from start to finish
insurance fluency on day one
pretrained on $400B+ of transactions
varies by team and account
how it learns your business
pretrained; configures to your specific guidelines
trained per team via SOPs, run-books, shadowing
time to insurance-fluent
day one
months per team
SME involvement to launch
light — agents arrive context-aware
heavy — UWs, claims handlers, ops leaders train the team
cost model
per-transaction agent pricing
FTE-based labor pricing
time to scale
instant
60–90 day ramp
accuracy profile
improves on a pretrained baseline
plateaus with team training
attrition risk
none
20–50% annually

built for insurance.
trained on insurance.
run by agents that already know it.

50+ insurance-native AI agents — Ingestion & Transformation, Validation, Document Classification, Triage, Integration, Summarization, Comparison & Recommendation, Flag & Action, and Document Issuance — achieve the same outcomes as a traditional, inside your systems, with a complete audit trail. Each workflow ships with insurance knowledge already loaded.
01.

submission intake and triage

multi-channel intake, NIGO checks, document extraction and classification, broker validation, account clearance, sanction screening, acknowledgement. Pre-loaded: SOV and loss-run structures, broker book conventions, NIGO criteria, appetite logic, authority matrices.
02.

underwriting assessment and pricing support

risk and loss summarisation, pricing tool prepopulation, price benchmarking against similar risks written, concentration risk flagging, FAC RI placement support. Pre-loaded: pricing tool conventions, line-size and concentration logic, FAC RI processes, portfolio benchmarks across major lines of business.
03.

quote

quote letter drafting with risk-specific clause selection, subjectivity suggestions, peer review prepopulation and routing, broker correspondence drafting. Underwriters retain authority on price, terms, and negotiation. Pre-loaded: clause libraries, quote letter conventions, subjectivity patterns, peer review rules, broker negotiation conventions.
04.

bind, book, and issue

bind order reconciliation against quote details, binder/cover note generation, contract certainty validation, premium/commission/tax calculation and ledger posting, invoice and policy wording generation, CAT modelling routing. Pre-loaded: contract certainty rules, regulatory tax tables, premium/commission/tax math, ledger posting conventions across jurisdictions.
05.

policy servicing and endorsements

PSR intake, complexity-based triage, compliance and sanction checks, financial and non-financial endorsement processing, ledger postings, document and invoice generation. Pre-loaded: endorsement types and complexity tiers, premium adjustment math, document templates by jurisdiction.
06.

claims FNOL and intake

multi-channel notification intake, completeness and duplicate checks, insured identification and policy match, claim number assignment, document indexing, urgency and complexity triage. Pre-loaded: FNOL formats across email, API, and portal channels; claim-to-policy match logic; completeness rules by line of business.
07.

coverage verification and triage

policy and endorsement retrieval, trigger and cause-of-loss validation, limit and aggregate erosion monitoring, adjuster routing where required, claim note prepopulation. Pre-loaded: policy structure and endorsement mechanics, coverage trigger logic by line of business, limit and aggregate erosion math.
08.

reserving

damage report findings, handling authority validation, initial reserve proposals benchmarked against similar historic claims, large-loss reporting, FAC and treaty net-down. Pre-loaded: reserving patterns by claim type, authority matrices, large-loss reporting workflows, FAC and treaty net-down logic.
09.

finance and reconciliation

premium accounting, broker statement reconciliation, claims payment processing, technical ledger postings, tax and commission calculations, with a full audit trail back to source. Pre-loaded: premium accounting structures, broker statement formats, technical ledger conventions, tax and commission tables by jurisdiction.

enterprise-grade by default.

  • SOC 2 Type II. Independently audited security and availability controls.
  • data residency. Configurable handling and retention by jurisdiction.
  • complete audit trail. Every decision queryable back to the source document.
  • model governance. Version control, change logs, and rollback for every workflow.
  • human-in-the-loop. Configurable review thresholds by workflow and risk.
  • SLA guarantees. Throughput, accuracy, and uptime commitments in contract.
  • exception escalation. Defined paths for edge cases and out-of-pattern work.
  • carrier-grade integration. Native connectors to policy admin, claims, rating, and finance systems.

frequently asked questions about mea Operations and insurance BPO

An AI-native BPO for (re)insurers. Carriers, MGAs, and brokers use mea Operations to run underwriting, claims, finance, and policy servicing end to end on insurance-pretrained AI agents — replacing labor-based BPO and avoiding the cost of training a generic agentic platform on your insurance knowledge.

Same category, different operating model. mea runs on insurance-pretrained AI agents, not labor-based teams. It costs less per transaction, scales instantly, runs continuously, and improves on a pretrained baseline instead of plateauing.

mea was built on insurance-native AI agents from day one. Incumbent BPOs are wrapping AI around an existing labor model. mea’s Knowledge Graph and DSLM are pretrained on $400B+ of insurance transactions, so the agents arrive context-aware — no months of training input from your underwriters, claims handlers, or operations leaders.

Generic agentic platforms ship as general-purpose reasoning engines. The carrier supplies the insurance knowledge — SOPs, run-books, taxonomies, broker conventions — months of SME effort before the first workflow is reliable. mea ships with that knowledge already in the platform: the Knowledge Graph carries the structure of (re)insurance, the DSLM is pretrained on $400B+ of transactions. Your SMEs validate; they don’t teach the platform what insurance is.

mea is powered by a proprietary Insurance Domain-Specific Language Model and Knowledge Graph, pretrained on $400B+ of carrier transactions and structured around the way insurance actually works. Foundation models require carriers and brokers to build the insurance fluency, integrations, governance, and operational scaffolding themselves. mea ships those capabilities pre-built.

Carriers looking for an alternative to traditional insurance BPO are increasingly choosing AI-native operations platforms.

First production workflow runs in weeks. Adjacent workflows move faster — integration, governance, and team enablement are already in place, and the agents are already insurance-fluent.

Lighter than clients expect. Internal teams shift from doing transactional work to overseeing it, with operator dashboards, exception queues, and reporting designed for ops leaders. Because the agents arrive insurance-fluent, your SMEs are not pulled into months of training.

see mea Operations in action

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