Let computers do computer work.
Let humans do human work.
Most organizations deploy AI as a product — a chatbot, a writing tool, a copilot — and find the workflows don't change. Mimir takes a different path: start with specific workflows, select the right intervention, build it, measure it, and expand from there.
If your team is doing work that computers should be doing, that's where we start.
[email protected] →The approach
Seven phases from orientation to expansion. One workflow proven before the next begins. The right tool selected for each job — simple automation when the problem is deterministic, machine learning when there's a pattern to find, a language model when judgment and language are involved.
You have to train your AI like you'd train any employee — with deliberate context, workflow knowledge, and iterative refinement. A general-purpose tool given no context produces general-purpose results.
Framework →The work
Manufacturing
Invoice Reconciliation
$14,200/mo recovered · 40 hrs → 14 hrs
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Logistics
Spot Quote Response
18.4 min → 5.9 min · +7 pts booking rate
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E-Commerce
Product Description Generation
~45 min → 8.4 min/SKU · 55% → 19% revision rate
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FP&A
Variance Commentary
9 hrs → 1.8 hrs/mo · 40% → 22% revision rate
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If your team is doing work that computers should be doing, that's where we start.
[email protected]