The Challenge
A SaaS company's support inbox was a flat queue, so urgent issues waited behind routine password resets.
Case Study · AI Integration
Cutting Support Response Time With AI Triage
A SaaS company's support inbox was a flat queue, so urgent issues waited behind routine password resets. An AI classification layer we built now auto-tags and routes incoming tickets by urgency and topic before a human ever opens them.
60%faster first response
NDA-protected engagement
The Story
What we walked into, and what we built
What We Built
An AI classification layer we built now auto-tags and routes incoming tickets by urgency and topic before a human ever opens them.
The Result
60%
faster first response
Client and platform names stay under NDA, consistent with the rest of our case studies — the engineering, and the outcome, are real.
How We Delivered This
The same path, every project
Clear stages, visible progress, and ownership that continues after launch.
01
Discovery
We map requirements, existing systems, constraints, and success criteria.
02
Architecture
Technical planning, risk review, and technology decisions documented before build.
03
Development
Iterative sprints with visible progress and working demos every sprint.
04
QA & Validation
Testing against real scenarios before anything reaches production.
05
Deployment
Controlled releases with rollback plans and zero-downtime where possible.
06
Support
Continuous improvement after launch, because production issues are our problem too.
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