Agentic layers over
your entire
manufacturing stack.
Your systems stay.
We add the layers that think.
Over every system in your stack we deploy two thin layers: a semantic layer that makes the system machine-readable in your company's vocabulary, and an agent application layer that acts on it. A cross-stack layer connects the three, enabling agents that reason end-to-end.
Semantic layer
Tag-to-asset graphs, unit conversions, SOP linkage, business terminology. The context every agent reads from.
Agent application layer
Specialized agents for the work on that system — RCA on SCADA, OEE on MES, margin analytics on ERP.
Cross-stack layer
Agents that pull context from every layer below to reason end-to-end. One investigation, all three systems.
The console your team
watches each shift
KPIs streamed from the MES layer, sparklines from the SCADA layer, and an agent activity log from the cross-stack layer — one console, all three.
OEE · Line 3
87.3%
+4.2ppFirst-pass yield
98.1%
+0.6Agent activity
One catalog per layer
Each stack layer gets its own set of agents. Start with one, add more as the semantic layer thickens and your team gets confident.
/ L1
SCADA / Historians
Agents that live on top of your sensors and historians — where the raw signal lives.
Sensor Cleanse
Removes noise, fills gaps, normalizes units
Alarm Rationalizer
Cuts floods, groups correlated events, proposes suppression
Asset Health
Vibration, temp, current trends → remaining useful life
Private models,
fine-tuned on your plant.
Frontier APIs are fine for demos and dead wrong for operations: your tag schema, your SOPs, your batch records are not someone else's training data. We run small, specialized models on your hardware — tuned to the way your plant actually talks.
Private by default
SLMs fine-tuned and served on your infrastructure. No data leaves the plant, VPC, or region.
No per-token bill
Inference cost is CPU/GPU cycles, not API calls. Agent chatter at scale stops being a line item.
Tuned on your data
Your tag naming, your shift language, your SOPs. The model learns the vocabulary of your plant.
We build the first layer.
Your team builds the next one.
Agentic infrastructure is a compounding asset only if your people can extend it. As we ship the initial agents, we train your leaders, general managers, and CDOs to build on the same semantic layer — so the second wave of agents comes from inside the org.
Pair-building
Every agent we ship is built side-by-side with someone on your team. The repo is yours; so is the review history.
Leaders, GMs, CDOs
Curriculum tuned for operational leaders — not just engineers. They drive the next-wave agent roadmap.
Handover-first
Semantic-layer ownership transfers as we deploy. By month six, your team is shipping agents without us.
What the layers
unlock in practice
-62%
Nuisance alarms
Alarm flood rationalization
Identified 400+ chattering alarms and generated suppression logic in one review cycle on the SCADA layer.
-78%
RCA time
Downtime investigation
Cross-stack RCA agent reduced multi-team investigations from 6 hours to under 10 minutes.
+18pp
Promise-date accuracy
Order-to-fulfil confidence
ERP agents reconciled with MES in real time, catching at-risk orders one shift earlier.
+4.2pp
OEE points
Packaging OEE uplift
Speed-loss attribution on the MES layer pointed to one upstream feeder; fix moved OEE from 82.1% to 86.3%.
$0
On SLM inference
Per-query cost
Fine-tuned small language models remove per-token cost; ROI curves stop flattening at scale.
Engineered for
plant-floor reality
No forced migrations, no ripping out your historian, no "move everything to our cloud." The stack you run today is the substrate we build on.
We stopped arguing about whose data was right. The agents surface a single, evidence-backed timeline — and the second wave of them came from our own team.
Operations Director
Tier 1 supplier · Discrete manufacturing
Ready to put layers over your stack?
Tell us what you run today — SCADA, MES, ERP. We'll map the semantic layer, the first agent pack per layer, and the enablement plan for your team.