Supercharging Industries
with Physical AI.
AICraft is the Physical AI Platform that senses, learns, predicts, reasons, and acts—empowering process industries to achieve consistent product quality, higher yield, reduced cycle times, and autonomous operational excellence — across batch and continuous processes alike.
Production value optimized
Industrial assets connected
Knowledge · Model · Agents
The problem we solve
Two batches, the same recipe, different outcomes
The signals that explain the gap already exist — scattered.
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85%
Batch loss prevented
Pharma
12%
Throughput gained
Batch mfg
3-15%
Energy reduced
APC
$15M
Per shutdown avoided
Refining
Step one · Knowledge
IT, OT and ET in one knowledge base
Three data worlds that normally never meet, unified before any model runs.
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The platform
Knowledge, model, agents
Three layers, each doing one job.
The outcome
What changes on the floor
Measured across batch deployments.
YIELD CONSISTENCY
BATCH CYCLE TIME
RIGHT-FIRST-TIME RELEASE
Domain expertise
Built for process industries
Designed around batch and continuous operations, not generic assets.
Chemicals
yield · cycle time
Pharma
golden batch · deviations
Oil & Gas
blending · campaigns
Utilities
treatment cycles
Energy
availability · maintenance
Process Mfg
throughput · energy
Customer stories
What it looks like in production
Two deployments, the same platform.
Early Batch Deviation Prevention
The Problem
One failed batch costs millions. Deviations are discovered only after batch completion, during quality testing.
SCENARIO: Slight agitation speed drift during crystallization alters particle size distribution — detected only during final QC testing.
What PilotX Did
Real-time batch telemetry → Live batch tracked against proven good batches → Abnormal patterns identified → Immediate operator alerts with the corrective setpoint.
Outcomes
85%
Batch Loss Prevention
70%
Faster Corrective Action
$650K–$1.8M
Annual Savings
Network-Level Loss Intelligence
The Problem
Losses accumulate gradually across zones. Control systems only see local measurements, never system-wide behavioural patterns. DMA inflow exceeds billed consumption by 12%.
What PilotX Did
Ingested network telemetry → Learned zone/feeder normal behaviour → Detected real-time loss patterns → Surfaced location, trend and monetary impact.
Outcomes
3–5%
Loss Reduction
$2M+
Emergency Repair Savings
40%
Regulatory Risk Reduction
Customers
Next step
See AICraft on your process data
We map the platform to your live batch or continuous records and show exactly where yield, quality and cycle time move — .