A leading IT services firm was facing a familiar challenge:
15 years of network issue documentation had created a sprawling, outdated knowledge base that engineers struggled to navigate.
Fixes were hidden across PDFs, wikis, and old tickets — hard to find, harder to follow.
Engineers spent hours digging through documentation instead of fixing issues.
Lack of centralized knowledge led to varied and inefficient resolutions.
High attrition meant expertise was constantly lost.
On average, engineers could only resolve 3–5 tickets per day, spending more time finding solutions than fixing problems.
Nanite.ai stepped in and built a specialized AI large language model trained on 15 years of remediation documentation.
Engineers ask in plain English — AI delivers proven remediation steps instantly.
Automated root cause detection and resolution within existing workflows.
Continuously updates SOPs by learning from resolved tickets.
Search time vanished — solutions now come instantly and consistently.
What once took hours of digging, now takes seconds — with far higher consistency.
Speed went up. Burnout went down.
With AI delivering instant SOP guidance and proactive remediation, engineers dramatically increased ticket resolution speed — without relying on tribal knowledge or senior hand-holding.
Productivity skyrocketed — engineers now close 15+ tickets/day.
Less dependence on senior team members to guide troubleshooting.
Institutional memory is now embedded and accessible to all.
Grafana integration accelerated detection and resolution cycles.
“It’s like every engineer has a senior mentor — one who knows every fix we’ve ever done and responds instantly.” — VP of Network Ops
AI trained on years of real-world SOPs delivers instant, reliable troubleshooting.
Fewer escalations, more consistency, better service.
AI preserves knowledge even as teams turn over.
Support volume grew — but the team size didn’t need to.
If your engineers are slowed by documentation overload or expertise gaps, we’ll build the AI brain that remembers it all — and acts.