AI Automation
Workflow automation, computer vision, and LLM agents that take real processes off people's hands — wired into the systems and devices you already run.
Explore AI automationMonocore Labs · Engineering Practice
Intelligent hardware,
and the automation that runs it.
We are a research-driven engineering studio working two disciplines as one: AI automation and hardware R&D. From the edge sensor up to the autonomous system, we build instruments operators depend on — not demos.
What we do
Hardware R&D
Embedded systems, sensor platforms, and autonomous tooling. Silicon, firmware, and the software that turns sensor output into something an operator can use.
Explore hardware R&DWhere the two meet
One stack, from the edge sensor to the model.
Most teams treat AI and hardware as separate problems handed to separate vendors. We don't. The interesting work lives where they meet — on-device inference, sensor data that feeds a model, automation that closes the loop back to a physical system. We build the whole path, so nothing gets lost at the handoff.
2Disciplines, one stack
10 HzGNSS + IMU capture
4-phaseDelivery method
Edge → CloudFull inference path
Selected work
Things we've shipped.
Product shot
AeroSync FDL1 logger
AeroSync FDL1 logger
Hardware R&D·Aerospace
AeroSync FDL1
A pocket-sized flight data logger and 3D replay system for trainer fleets. Records the whole sortie on a single switch.
Project shot
Vision inspection cell
Vision inspection cell
AI Automation·Industrial
Line-Side Vision QC
An edge computer-vision cell that flags surface defects in real time and logs every reject for traceability.
Project shot
Telemetry pipeline
Telemetry pipeline
AI Automation·Hardware
Telemetry Copilot
An LLM agent that turns raw device telemetry into plain-language debrief notes for field operators.
How we work
Four phases. No surprises in the last one.
The same disciplined path whether the deliverable is a firmware image, a trained model, or a board you can hold.
PHASE 01
Research
Constraints, data budget, and the measurement question that defines the system.
PHASE 02
Prototype
Bench rigs, firmware skeletons, model baselines — the first build that turns the answer on.
PHASE 03
Validate
Field trials with the operator. Logs reviewed, edges hardened, tolerances confirmed.
PHASE 04
Deliver
Production unit, documentation, and a clear path to the next revision.
Let's build something precise.
Hardware briefs, automation work, and research collaborations — we read every one.