Let's face it... Most AI experiments die after the demo.
The demo looks great in a clean sandbox. Then reality hits, and it breaks in the same three places every time.
The integration never happens.
The prototype looks great until it has to write real records, handle permissions, and fit your actual workflow. That's where most projects stall.
Edge cases continue to pile up.
Real inputs are messy. Weird PDFs, forwarded threads, missing fields. Without someone owning the fallback path, people quietly revert to manual work.
It dies without anyone noticing.
No monitoring, no runbook, no owner. The system degrades until someone turns it off. Six months later, you're back to spreadsheets.
We build the parts that make AI actually stick.
Every project ships with:
Automation that integrates
Real workflows into real systems: CSV/API outputs, records, routing, and handoffs.
Exception handling built in
Human-in-the-loop paths, validation rules, and a queue for edge cases.
Monitoring and a runbook
Alerts, ownership, and docs so the system survives past launch.