Execution intelligencefor automated labs
So you know what actually happened before the run leaves the bench.
See
Live run context from the systems you already use.
Catch
Execution drift and likely failures before downstream QC.
Prove
Trace execution to outcomes with evidence-ready timelines.
Opens a short access page: enter your demo code, then the live environment opens in a new tab. Not a public sandbox.
The Problem: The Loop Nobody Talks About
Automation got faster. The blind spots stayed the same.
Moment 01 · Silent failure
A 384-well screen starts clean. Hours in, something drifts. The instrument still logs “step complete.” Nobody knows yet.
Moment 02 · Late discovery
The issue appears at post-run QC. Plate is gone. Run is lost. The team spends days reconstructing events across disconnected systems.
| What automation promised | What labs actually do |
|---|---|
| Autonomous overnight runs | Scientists babysitting instruments |
| Automation engineers building new systems | Automation engineers on call, watching logs |
| Real-time error detection | Post-run QC discovering failures hours late |
| One source of truth | Logs fragmented across 5+ systems |
| Multi-day trend detection | Errors invisible until they cascade |
The robots got better. The software got better. The measurement layer — knowing what actually happened in real time across every data source — was never built.
What Sensai actually does
A measurement layer that fuses machine events, workflow context, and visual evidence into one run narrative.
Scheduler
Run steps, queues, state
LIMS
Samples, plates, lineage
Instruments
Liquid handlers, readers, logs
Vision
Deck, tips, labware
Sensai
Correlate · detect · explain
Spotlight
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