Socotra introduces AI-driven insurance configuration
October 13, 2025
Socotra has launched Agentic Configuration, an AI-driven way to build and manage insurance product configurations using natural language. For product teams, the pitch is straightforward: ship faster, cut costs, and reduce the dependency on scarce engineering bandwidth.
Built on the cloud-native Socotra Insurance Suite, the capability plugs into flexible data models, product inheritance, open APIs, and fully published documentation. The goal is to move from idea to testable product without fighting the tooling.
What Agentic Configuration does
Using conversational AI, business teams can capture requirements, configure products using Socotra's best practices, and validate and deploy configurations to test environments. It lowers the barrier to entry so non-technical users can contribute without breaking guardrails.
- Natural language configuration for coverages, rating, and rules
- Built-in best practices and product inheritance to stay consistent
- Automated validation and deployment to sandboxes
- Governance controls so changes are reviewable and auditable
Why this matters for product development
Socotra reports teams can cut configuration and testing timelines by 50%, reduce development costs by 75%, and decrease prototype iteration time by up to 90%. That means faster market tests, tighter feedback loops, and fewer handoffs.
- Move from concept to a testable configuration in weeks, not months
- Let business teams own early iterations while engineers focus on complex work
- Standardize product structures across lines to reduce rework
- Lower vendor wait times by keeping more iteration in-house
How it fits your stack
Agentic Configuration extends Socotra's MCP Server, which enables instant integrations between the Insurance Suite and agentic AI tools like Claude and Cursor. Together, these pieces make AI a native part of product design, testing, and deployment-not an add-on.
Implementation checklist
- Select 1-2 products for a controlled pilot (one simple, one moderately complex)
- Define guardrails: approval workflow, versioning, and rollback policy
- Prepare data models and import any reusable components for inheritance
- Stand up dedicated sandboxes and CI for configuration validation
- Train business analysts on prompt patterns, edge cases, and exception handling
- If your team needs structured upskilling, see AI courses by job role
- Instrument metrics: cycle time, defects per release, cost per iteration, time-to-market
- Run a weekly review cadence with underwriting, actuarial, and compliance
Risks and controls
- Model errors: require human review before promotion to higher environments
- Traceability: enforce version control, change logs, and approvals
- Data security: ensure no sensitive data is exposed in prompts or logs
- Governance: align configuration changes with pricing, filing, and compliance requirements
- Change management: set clear roles between product, engineering, and operations
What Socotra says
"Insurance companies are under immense pressure to innovate quickly while facing a shortage of technical talent," said Socotra chief operating officer Ekine Akuiyibo. "With Agentic Configuration, insurers can move from product concept to testable configuration in weeks instead of months. This capability democratizes product development, promotes AI literacy, and unlocks the creativity of business teams without sacrificing accuracy or governance."
For product leaders, the takeaway is clear: shorten cycles, bring configuration closer to the business, and keep oversight tight. If the reported gains hold in your environment, this is a practical path to quicker launches and leaner iteration.
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