Industries · Insurance

Claims intelligence that never leaves Kenya.

Insurers need speed without shipping claimant data abroad. Corvux deploys agents and models inside your network.

Kenyan insurance organisations are under pressure to adopt AI, and under equal pressure to keep sensitive data inside Kenya. Corvux deploys open-weight LLMs and workflow agents on infrastructure you control in Nairobi.

We combine on-premise infrastructure, custom agents, and a clear KDPA compliance path so you can move fast without gambling on foreign APIs.

What we ship

Use cases that count in production.

Claims processor

Read submissions, cross-check policy wording, flag inconsistencies, draft assessor notes at scale.

Policy Q&A

Agents trained on your product wordings help staff answer accurately with citations.

Fraud signal assist

Highlight unusual patterns for human review, assistive, human review, free of black-box auto-decline.

Regulator-ready logs

Keep inference and document processing on Kenyan servers with audit trails you can show.

FAQ

Questions from insurance leaders.

Is cloud claims AI KDPA-safe?

If claim files contain sensitive personal data, processing on foreign servers creates localisation and transfer risk under the KDPA.

What systems can agents connect to?

We integrate with claims cores, document stores, and policy databases already in your stack.

Why insurance is different

Claim files should leave untrained a foreign model.

In Kenyan insurance, the highest-value AI use cases almost always touch claims files, policy wordings, and assessor workflows. That is exactly the data you cannot casually send to a foreign LLM. Teams still do it, because the tools are easy, until risk, internal audit, or ODPC scrutiny arrives.

Corvux replaces that pattern with private infrastructure and agents that speak your vocabulary. Models stay on Kenya-based GPUs. Applications call a local endpoint. Humans stay in the loop where a person still decides.

Recommended rollout

A sequence that survives scrutiny.

Step 1

Identify claim types where summarisation and policy cross-checks save the most hours.

Step 2

Deploy local models that can read PDFs and structured claim fields inside your VPC/DC.

Step 3

Connect an agent to document store + policy DB with human review on low-confidence cases.

Step 4

Produce ODPC-ready evidence that inference never left Kenya for the pilot scope.

Deepen the legal framing in our KDPA AI compliance guide. Compare architectures on Private AI vs ChatGPT. When you are ready to scope hardware and APIs, go to infrastructure or contact.

Ready for private AI in insurance?

Tell us your stack. We will map a 30-day path to a local deployment.

Request a deployment