No-code Industrial AI for chemical producers.
Impurity drift only shows up in the lab, separation trains burn most of your energy, and your DCS alarms have lost the operators' trust.
The operating pressures we built around.
Quality on impurities
Specs are tight and lab feedback is slow relative to the process.
Energy-intensive separations
Distillation and drying dominate site energy use.
Alarm flood on continuous units
Threshold alarms multiplied over decades; signal-to-noise is poor.
The work that pays for itself first.
The platform capabilities that matter most here.
- Model builder →
Soft sensors for impurities and key qualities.
- Prescriptive optimization →
Column and reactor setpoint guidance.
- Anomaly detection →
Reactor and rotating equipment monitoring.
Adjacent proof — specialty chemicals site
"One Intelecy model replaced four threshold alarms — same coverage, a fraction of the noise."
What we read, how often, and how it gets here.
Historian (PI/AVEVA/AspenTech), DCS, LIMS, MES
T, P, flow, level, density, online analyzers, lab results
1–5s for control; per-sample for LIMS
Historian + LIMS via Gateway. Write-back governed per loop and per safety review.
Reporting and audit, built into the workflow.
REACH & product safety
Process and quality records aligned to substance documentation.
PSM / process safety
Model-driven alerts integrated into existing safety governance.
Sustainability reporting
kWh and CO2 per ton, per unit, exportable to ESG tooling.
One-pager for chemicals teams.
A printable summary covering the use cases, expected KPIs, data needed, and integration notes on this page — written for plant leadership and IT/OT.
See it on your own chemicals data.
A 30-minute working session with an industry specialist. Bring one unit and your top KPI — we'll come back with a working model proposal.