A Lightweight Framework for Evaluating LLM Assistants in Production
A practical, low-cost evaluation loop that small product teams can run on every release of an AI feature.
Read moreWhere growing teams lose time, which workflows they automate first, and what separates projects that stick from those that stall.
Abstract
We analysed the automation projects we delivered and scoped with small and mid-sized teams to understand which processes are automated first, how long they take to pay back, and why some projects fail to reach adoption.
Key findings
This report summarises patterns from automation projects delivered and scoped by Orbiht. It is a practitioner's view, not a statistical survey, and should be read as such.
Across teams, the biggest time sinks were not complex tasks — they were hand-offs: copying data between tools, chasing approvals and assembling reports.
The most common reason was not technical. It was the absence of an internal owner who kept the workflow updated as the business changed.
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