Case Study

Intelligent Automation Case Study | Insurance & Financial Services

RPA + AI ReasoningFrom rule breaks to adaptive workflows

Client Profile

An insurance and financial services company running high-volume back-office workflows across claims, policy administration, and compliance processes.

The Problem: Rules-Based RPA That Broke the Moment Anything Changed

The client’s existing RPA scripts automated the happy path well, but the real world doesn’t stay on the happy path. A slightly different document layout, an unexpected field value, or a process exception outside the original script’s assumptions would break the automation outright, sending the case back to a person and, often, requiring an engineer to patch the script before it could run reliably again.

Failure Point Business Impact
Rigid rule-based scripts Any deviation from the expected format breaks the automation
No handling for edge cases Exceptions fall back to fully manual processing
Frequent script maintenance Engineering time spent patching brittle automations instead of building new ones
Inconsistent exception handling Similar edge cases get resolved differently depending on who handles them

The Solution: An Automation Platform That Reasons Through Exceptions Instead of Breaking on Them

ISZ.AI built an intelligent automation platform that combines RPA with AI reasoning, so workflows can adapt to edge cases instead of stopping dead the moment something doesn’t match the script.

  • RPA for the Structured Work: Deterministic, auditable automation still handles the well-defined, repeatable parts of each workflow.
  • AI Reasoning for the Exceptions: When a case falls outside the script’s assumptions, an AI reasoning layer interprets the situation and determines the appropriate next step instead of failing the automation.
  • Consistent Exception Handling: The same reasoning logic is applied every time, so similar edge cases are resolved the same way regardless of when or how they arrive.

The Results: From a Point Automation to a Core Offering

  • Workflows that adapt instead of break: Brittle rule-based automation was replaced with a platform that reasons through exceptions rather than failing on them.
  • Adopted beyond the original use case: The platform is now a core offering across the client’s enterprise client portfolio, not a one-off automation for a single process.
  • Less engineering time on maintenance: Fewer broken scripts means less engineering time spent patching automations and more spent extending them to new workflows.

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