Field notes from production AI.
What we learn shipping — written up for the next team solving it.
LLM vs SLM: which AI model fits your business?
Not every problem needs a 70B-parameter model. A practical framework for choosing between a large language model and a small one — and what that choice costs.
Read →Field notes: RPA for small teams, done right
You don't need an enterprise license or a ten-person CoE to automate. A practical starting playbook from a dozen mid-market engagements.
Read →How to scope your first AI pilot in 30 days
A week-by-week playbook for teams moving from idea to shipped pilot — what to cut, what to keep, and how to avoid the six-month discovery trap.
Read →The data layer most teams skip — and regret
Before you train a model or wire an agent, get the plumbing right. A field guide to the contracts, lineage, and quality checks that decide whether AI ships.
Read →Automation that sticks: owners, not orphans
Half of automations rot within a year. The fix isn't better tech — it's naming an owner, writing the runbook, and budgeting for maintenance from day one.
Read →Inside Binary Lab: how we ship production AI
The working methods behind our engagements — how we scope, staff, and instrument so the system is live in weeks, not quarters.
Read →Ready to build something great?
Whether exploring what's possible or ready to launch — our team responds within 24 hours.
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