Indico Data

Indico Data solves the problem of a large amount of unstructured material in insurance operations that is difficult to access into the system. Underwriting, claims, policy reconciliation, and brokerage reconciliation often rely on emails, PDFs, forms, scans, and attachments, and Indico Data uses AI to receive, extract, judge, and orchestrate downstream.

Insurance documentation and process automation

From Confusing Material to Available Data

The platform targets submissions, claims, SOV, loss run, and other materials, and organizes unstructured content into data that can be used by downstream systems. For teams dealing with a large number of insurance documents, this reduces manual entry and back-and-forth reconciliation.

Agentic AI supports high-friction processes

Indico Data emphasizes high-friction workflows such as underwriting, claims, and service changes. AI not only identifies fields, but also sends data to the right process nodes, allowing business work to continue to advance downstream.

Enterprise security and architecture

These tools often involve customer, policy, claims, and financial information, so they require attention to security architecture, permission controls, audit trails, and manual review. Organizations should be evaluated with compliance, IT, and business teams before deployment.

Which organizations are suitable

• Commercial insurers can automate the receipt and collation of underwriting materials.
• Claims teams can reduce the stress of documentation and initial classification.
• Financial services teams can handle complex unstructured documents.
• Large operations teams can integrate AI into existing core systems and work queues.

FAQs

Is Indico Data a universal OCR tool? **

not. It is more focused on the receipt, extraction and process orchestration of insurance and financial services, focusing on converting document content into data that can be accessed into business systems.

Can it completely replace manual review? **

No, I can't. Insurance underwriting, claims, and compliance judgments require a manual chain of responsibility, and AI is suitable for reducing entry, classification, and preprocessing efforts.

Which files are best for processing? **

Submissions, loss records, SOVs, mail attachments, forms, and scanned documents are all suitable. The more complex the file, the more clear fields, confidence, and review rules need to be set up.

What should enterprises prepare before accessing? **

It is necessary to review existing processes, document types, target systems, permission requirements, and review criteria before evaluating the security architecture and integration methods.