We don't replace
your stack.
We put layers over it.
ContextWeaver is an agentic-infrastructure company for manufacturing. We build the semantic and agent-application layers that sit over your SCADA, MES, and ERP systems, train your team to extend them, and then we leave.
Why this company exists
Every conversation on a plant floor eventually comes back to the same two sentences: "We already have all the data." And: "We still can't trust what it says."
The problem was never the data. It was the absence of a layer between the data and the people that turns raw signal into context the organization can act on. That layer has always been built by hand, once per question, and thrown away when the question changed.
ContextWeaver makes that layer a first-class piece of infrastructure. A semantic layer your company owns, agent applications that read from it, and a cross-stack layer that lets any one of them reason end-to-end. Private models on your hardware, and a training path so your team extends the work after we're gone.
What we believe —
and what we won't compromise on
The semantic layer is the moat
Frontier models are commodities. Your plant's vocabulary, tag ontology, and SOP corpus are not. We invest in the layer no one can copy — the one that describes how your operation actually works.
Your data never leaves your infra
Small language models, fine-tuned on your data, served on your hardware. No egress, no per-token bill, no vendor dependency on someone else's roadmap.
Enablement beats dependency
We deliberately work ourselves out of a job on the first wave. The engineers, GMs, and CDOs we work with leave the engagement shipping agents without us.
Brown-field is the default
You already spent a decade building the stack. We build on top of it, not around it. No rip-and-replace, no forced migration, no re-architecture projects.
Transparency over magic
Every inference the platform makes is traceable to the sensor reading, batch record, or ERP line item it came from. Operators should never have to trust unexplained output.
Leaders, not just engineers
Agentic systems fail when they're an IT side-project. The people we train are the people who run the plant — GMs, ops directors, CDOs — because they're the ones who know which agents should exist.
How we got here
Time spent on plant floors listening to engineers describe the same problem: every analytics tool assumes clean data, and almost no plant has it.
First semantic layer built for a process plant. Cross-stack RCA agent shipped before shift end became the template for everything after.
Agent catalog expanded to cover all three stack layers. Small-language-model fine-tuning replaced frontier APIs for plant workloads.
Every engagement now ships with a training curriculum. The second wave of agents at each client comes from their own team.
Who we build with
Not every manufacturing org is ready for agentic infrastructure. The ones who are tend to share a few traits.
Stack-literate operators
A plant team that already knows which data lives in which system, and is frustrated that the systems don't talk.
A mandate from the top
GMs, CDOs, or ops directors who own the outcome — not a standalone IT project with no operations sponsor.
Appetite for ownership
Teams who want to extend the platform themselves, not teams looking for a permanent vendor dependency.
Want to see if we're a fit?
Tell us the shape of your stack and the outcomes that matter most. We'll sketch a first-layer plan and an enablement roadmap for your team.