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How long does lab automation take to deploy?

Why off-the-shelf workflows run in weeks and novel ones take far longer — the "march of nines."

By Robot on Rails · Updated 2026-06-23

Short answer

It depends almost entirely on novelty. An off-the-shelf workflow on proven hardware can be running in days to weeks. A genuinely new workflow takes much longer — not because the first version is hard, but because reliability is: getting to 90% is quick, and each additional nine (99%, then 99.9%) takes roughly as much effort again. Budget for the nines, not the demo.

Two timelines: off-the-shelf vs novel

The single biggest predictor of deployment time is whether you're running a known workflow or inventing one:

The march of nines

A demo that works 90% of the time looks finished. It isn't. Each extra nine of reliability — 99%, then 99.9% — tends to cost about as much effort as everything before it, because you're now handling the rare edge cases that only appear at scale.

Reach 90%
Reach 99%
~2×
Reach 99.9%
~3×
Illustrative: each added nine of reliability roughly repeats the prior effort — the "march of nines."

Why new workflows drift

New workflows drift because new requirements keep appearing — an edge-case sample, a reagent that behaves differently, a step that needs a tolerance no one specified. The first 90% is the part everyone imagined; the last stretch is the part nobody did. That's normal, and planning for it is the difference between a deployment that lands and one that stalls.

How to deploy faster

See the common failure modes →

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