~14 days
of senior capacity unblocked.
Freed architects from minor fixes to focus on higher-value system decisions and remediation.
How Agentic AI Helped a U.S. Life Insurer Accelerate Legacy Platform MaintenanceHow Agentic AI Helped a U.S. Life Insurer Accelerate Legacy Platform Maintenance
Introduction
Exadel deployed Exadel Colleague AI to triage and automate eligible maintenance tickets through a governed, test-backed workflow in Jira/Git—without losing human control.
Description
Label
From Vague Tickets to Verified Fixes
The U.S. life insurance and wealth management provider's .NET application had entered sunset maintenance, where the real cost isn’t the fix, it’s the missing context. Tickets arrived with ambiguous descriptions and hidden dependencies, forcing engineers to reconstruct intent and impact before touching code.
By integrating Exadel Colleague into the existing repo and test suite, we made those “small fixes” faster by reducing time lost to context reconstruction and validating changes through predictable test blocks.
This is the first paper in a three-part series. Whitepaper 2 covers Operational Excellence. Whitepaper 3 covers Implementation, Roadmap, and Cloud Deployment.
Impact at a Glance
Backtested on historical tickets to prove value with zero production risk.
Customer expectations
Clients expect loyalty, transparency, and seamless digital interactions.
111 human-equivalent hours recovered
Across 21 AI-eligible tickets for $32.50 total API cost ($1.55 avg/ticket)
81% cycle-time reduction
Across AI-eligible tickets in the backtest evaluation
90% accuracy on high-volume categories
Strong performance on repeatable ticket types (“Full Pass”)
Projected $110K annual capacity value
Assuming recurring use across ~25 maintenance sprints/year (per model provided)
The Challenge. Why maintenance mode became a delivery risk.
Backlog tickets lacked context
Vague descriptions, layered dependencies.
Quality overhead increased
Critical errors, including a production QA failure.
Onboarding bottlenecks
New engineers needed weeks/months of core team time.
How Exadel delivered leverage
Exadel Colleagueaccelerated eligible maintenance work through Jira/Git—governed, test-backed, and human-controlled.
Risk-managed backtest:
cloned repo + historical backlog, zero live disruption
Agentic SDLC workflow:
Analytical → Programming → Testing agents (TDD/BDD)
Human control retained:
engineers reviewed, approved, and merged changes
Test-backed delivery:
predictable verification blocks for repeatable tickets
Proven Solutions
Evidence & Performance
We validated Colleague on historical tickets in an isolated environment—then measured performance by work type.
Assess
Backtest + triage
Accelerate
Agents + tests
Control
Human review gate + routing
35 historical tickets evaluated
Baseline created using historical backlog.
21 tickets AI-eligible
Routed through Exadel Colleague.
14 tickets kept in the human route
Marked ineligible and handled by engineers.
Frontend user stories
70% success (7/10) • 90 hours recovered
Easy bug fixes
56% success (5/9)
Backend user stories
20% success (1/5)
Hard bug fixes
18% success (2/11)
Let’s turn your maintenance
into repeatable delivery
with Exadel Colleague.
Case Studies
