Logswiz applies LLM reasoning to 100% of your sensor telemetry, detecting failure signatures, quality deviations, and predictive patterns before they become defects or recalls.
No credit card required · Up and running in minutes
Manufacturing floors generate millions of sensor events every second. To manage storage and processing costs, teams sample down to a fraction. The failure signature that precedes a recall is almost always in the data they dropped.
90%
Of sensor data typically unanalyzed
Cost of storing and reasoning over all sensor data leads teams to sample aggressively. Failure patterns hide in that 90%.
$18M
Avg. cost of a product recall
Most recalls have detectable precursor signals that were present in sensor data hours or days before the defect manifested.
100%
Logswiz sensor coverage
Every sensor event reasoned over by LLM intelligence. Failure signatures detected before they become defects.
What becomes possible when LLM reasoning runs over 100% of the data.
A global automotive parts manufacturer detected a fatigue failure signature in sensor data 18 days before the first field failures occurred — enabling a targete...
Read More →A European semiconductor fab reduced unplanned downtime by 78% — recovering $31M in annual production capacity — by applying LLM reasoning to 100% of equipment ...
Read More →A consumer goods manufacturer achieved Six Sigma quality on a production line that had never broken below 3.2 sigma in seven years — by identifying a cross-sens...
Read More →Ingest from PLCs, SCADA systems, IoT sensors, and any industrial data source. 100% of events, no sampling policy.
LLM intelligence analyzes each sensor event, identifies drift patterns, and correlates cross-sensor signals that predict failures.
Failure predictions, quality alerts, and maintenance signals with full reasoning traces delivered in real time.
Connect to your manufacturing execution system, CMMS, or quality platform via standard APIs. No infrastructure overhaul.
1000× y
Cost to reason over x volume of data
y
Same x volume. Same reasoning. Fraction of the cost.
Inference cost ratio
1000×
less to reason over the same data
Which means
Full coverage
becomes viable
// SAME MODEL. SAME OUTPUT. 1000× THE ROI.
The value Logswiz delivers comes from two compounding factors: the volume of sensor events it reasons over that were previously dropped, and the reliability of the output that makes LLM inference genuinely trustworthy.
Together they produce a return on investment that reframes the question entirely, not "can we afford to do this?" but "what has it been costing us not to?"
Get Started Free →See what 100% sensor data coverage looks like for your production floor, with a model reliable enough for production.