What we find, what we build, what breaks.
Market intelligence and trend analysis. Where AI is heading, what's hype, and what matters for operators.
Anonymized patterns from real discovery engagements. What we actually find when we interview your team.
Frameworks, how-to guides, and decision tools. Build the business case before you build the system.
Failed automation teardowns. What went wrong, why it went wrong, and what the fix actually looks like.
Every company has them. The Excel spreadsheet that runs the warehouse. The personal Gmail that handles vendor approvals. The Slack channel that replaced the ticketing system. They're not bugs — they're symptoms of tools that failed the people using them.
Most companies don't realize their automation layer is one API change away from total failure. We see it in every discovery — 40, 60, sometimes 100+ Zaps held together by institutional memory and prayer.
You don't need us to build the initial case. You need three numbers: hours burned weekly, loaded salary cost, and error rate. Here's the framework we use internally — and you can run it yourself before ever picking up the phone.
The vendor promised seamless integration. The timeline was 8 weeks. The budget was $200K. Ninety days later, the sales team was back on spreadsheets and the CFO was asking hard questions. Here's the autopsy.
In every discovery engagement, there's a moment where the contradiction becomes undeniable. The CEO says the ERP rollout went smoothly. The warehouse lead says they abandoned it three weeks in. Both are telling the truth — about different realities.
RPA clicks buttons. AI agents make decisions. The marketing conflates them constantly, and the confusion costs companies real money when they buy the wrong solution for their actual problem.
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