AI solutions for insurers, brokers and claims teams, with policy-linked evidence, human approvals, controlled data access and regulatory review.
Built for regulated work
For insurers, reinsurers, brokers and third-party administrators. Connect policy records, claims and customer service without giving a model authority over coverage, payments or customer rights.
Use AI to read, organise and prepare evidence where it saves meaningful effort. Keep rules, permissions and calculations in tested software, not in a prompt.
Translate requirements agreed with legal, compliance and business owners into acceptance checks, approval points and operating procedures.
Compliance depends on the entity, licence, activities, contracts and actual operation. We build technical controls and evidence, not legal advice or regulatory certification.
Four practical solutions
Start with one workflow, approved sources and a named owner. These are solution examples, not claims about past results.
Read claim forms, invoices, reports and policy documents. Extract dates and amounts, identify missing evidence and prepare a source-linked case summary. Flag inconsistencies for investigation rather than treating them as proof of fraud.
Approval boundary. Claims staff decide coverage, settlement, rejection and payment approval.
Organise submissions, extract risk information and compare it with approved underwriting guidelines. Tested software calculates values and applies agreed thresholds. Underwriters can inspect the evidence behind each flag.
Approval boundary. Authorised underwriters approve risk acceptance, exclusions, pricing and exceptions.
Answer routine questions using the correct policy wording and version. Draft service replies, track required documents and route complaints. Separate a general explanation from a binding coverage interpretation.
Approval boundary. Ambiguous coverage, complaints and changes to cover go to authorised staff.
Collect expiring policy records, prepare renewal packs and reconcile premium and commission data. Assemble review evidence for customer due diligence and reporting from approved systems.
Approval boundary. Staff approve renewal terms, financial adjustments and regulatory submissions.
How the work flows
Each output stays linked to its sources. Failed checks or missing evidence send the work to a person. The approval record is separate from the AI draft.
Retrieve the policy, schedule, endorsements and effective dates for the actual case. Record document versions. If coverage evidence conflicts or is incomplete, stop and request review.
Do not let AI autonomously deny claims, set premiums, cancel cover or release payments. Keep preparation, decision approval and payment authority separate.
Evaluate outcomes across relevant customer groups where lawful and supported by sufficient data. Document limitations and provide a named route for complaints and reconsideration.
Apply case-level access to medical, financial and identity records. Minimise what reaches the model and keep sensitive data out of unnecessary logs.
Regulatory scope
Identify the regulator, licence, markets and data before implementation. The references below are starting points for assessment, not a declaration that every rule applies.
For UAE insurance activities, confirm the CBUAE requirements applicable to the licence, distribution model, claims process, outsourcing and customer protection. Brokers and insurers do not necessarily have identical obligations.
CBUAE RulebookFor DFSA-regulated firms, map the relevant conduct, systems and controls, prudential and AML requirements to the permitted activities. A UAE-wide rule list is not a substitute for this licence-specific assessment.
DFSA RulebookAssess applicable privacy law, health-data restrictions, transfers and retention. Where DIFC Regulation 10 applies, review its requirements for personal data processed through autonomous and semi-autonomous systems.
DIFC Regulation 10Under the EU AI Act, AI intended for risk assessment and pricing in life and health insurance can fall within the high-risk category. Assess intended use, exceptions, territorial scope and phased application dates rather than classifying every insurance tool alike.
EU AI Act, Annex IIIYour legal and compliance teams confirm current rules, applicability, effective dates and supervisory expectations. Engineering evidence supports that review; it does not replace it.
Data protection and reliability
Review retrieval, providers, tools, uploads, activity records and support access together. A private model can still be unsafe if the connected workflow is not controlled.
Assess approved cloud, private infrastructure or self-hosted models against data sensitivity, outsourcing, support access and transfer requirements. Client data does not train general-purpose AI without express written agreement.
Record source references, model and policy versions, tool calls, checks, reviewer and outcome. Protect activity records from unauthorised changes and agree retention with the responsible teams.
Test missing evidence, stale sources, duplicate requests, provider outages and rollback. Stop at failed checks and route the case to a person without blocking the established process.
Test model, prompt, retrieval and integration changes against agreed cases. Track errors and review overrides after release. Provide named owners, an incident procedure and a controlled rollback.
Connected to your existing systems
Start with narrow read access. Any write is separately authorised, validated and recorded. Agree reconciliation and failure handling before connecting production records.
Read policy administration, claims management and broker systems through approved interfaces. Preserve policy IDs, endorsement history and claim status as the source of truth.
Connect authorised document stores, email and service queues. Scan uploads, isolate untrusted document instructions and retain links to the original evidence.
Reconcile premium, commission and settlement records using tested calculations. Use approved screening providers for due diligence, with separate approval for any write.
Delivery and handover
Identify the licensed entity, activities, markets and records. Your legal and compliance teams confirm applicable obligations and required approvals.
Agree inputs, outputs, access, review points and prohibited actions. Define measurable pass criteria and the evidence needed for release.
Connect approved sources and test representative cases, difficult exceptions, source accuracy, permissions, calculations and security attacks.
Run AI-prepared work alongside the current workflow. Business and risk owners review results without authorising new customer-impacting actions.
Hand over agreed code, configurations, control mapping, evaluation evidence and operating procedures. Confirm monitoring, support and change approval.
Scope, ownership, licensing and support terms are agreed in writing. We estimate delivery after reviewing access, integration and approval dependencies rather than promising a regulated production date in advance.
Questions before starting
Our proposed workflow prepares the evidence and highlights relevant policy wording. An authorised claims reviewer decides coverage and settlement. Missing or conflicting evidence is escalated, not resolved by a confident-sounding answer.
Only after confirming permitted processing, access, deployment and provider terms for the specific records and jurisdiction. We minimise data, enforce access and test handling controls. Private hosting alone does not establish lawful processing.
No. Existing policy and claims systems remain authoritative. We add controlled preparation and review workflows through approved integrations.
Use authorised representative cases to measure field extraction, policy citation accuracy, missed evidence and incorrect flags. Include difficult cases, access tests, document attacks and human-review outcomes.
Start with one process
Tell us about the records, the systems and the rules involved. We will help define a first release and the evidence needed to review it.