899B
SRAM, including stack
Fixed-size experience profile, measured on an emulated ATmega328P.
Local intelligence.Real-world decisions.
Explore the possibilitiesSmall footprint.
Room for intelligence.
4,216B
Flash footprint
Code and data for the same bounded AVR experience profile.
≤5ms
Per query
2.57–4.99 ms at 16 MHz, including RMS comparison and sorting.
0
GPUs required
CPU-only computation in the reported native and AVR experiments.
Beyond thresholds. Toward understanding.
Learn the device.
Not just the category.
Build a memory of confirmed operating examples from the actual unit, installation and load. Match new signals against that local experience.
Refine the part
that changed.
Update a response map where new measurements disagree. In the tested function maps, distant predictions stayed unchanged.
Make “unknown”
a useful answer.
Flag inputs outside the learned examples and request review instead of forcing a familiar label onto an unfamiliar signal.
Check the answer.
Before the action.
Check proposed settings against explicit operating limits. Keep a separate path for an inadmissible or unsupported result.
Intelligence within
a device budget.
Select the mechanisms your hardware can support. Put compact readouts on a microcontroller and larger models on a local gateway.
Keep the decision
close to the signal.
Run the selected decision logic locally. Connect learning, response models and action checks without making every inference a cloud request.
More experience. Same device.
Change the conditions. Teach a new response. Watch the same device reach its target again.
Adaptive flow controlNormal pressure
Simulated valve · flow shown in relative units
Known conditions · experience reused
Right flow. Known conditions.
The stored response provides the opening for the target flow. Change the pressure to test a different condition.
Target flow50
Actual flow50
Valve opening71%
123Measure → learn → adapt
1 learned response✓ Normal pressure
Higher pressure → lower pressure → normal
Engine trace
Change pressure to inspect the engine response.
Teach the device. Keep the experience.
Start with examples from your equipment. Use confirmed feedback to expand what it recognizes, then test the updated behavior before putting it to work.
Capture examples
Record signals, operating context and confirmed outcomes.
Learn locally
Build a compact memory or a response map for the device.
Check new inputs
Compare with learned experience and explicit limits.
Confirm and refine
Review unfamiliar cases, then update and recheck.
Observe. Learn. Check. Refine.
Combine functions.
Build useful devices.
Turn separate measurements into a decision workflow. Combine experience, numerical models and explicit checks to suit the job.
Signal memory
Recognize familiar operating patterns and flag unfamiliar inputs.
Response models
Estimate how a device will respond to a proposed setting.
Action checks
Check whether the proposed setting stays within defined limits.
Give existing hardware a new job.
Explore device-specific applications with your engineering team. Match the function, memory budget and validation to the equipment.
APPLICATION TO EXPLORE
Motor & pump modules
Recognize operating patterns from current or vibration. Flag an unfamiliar signal for review, then add a confirmed example to the local memory.
Current · vibration · operating contextState · similar examples · unknown
One AI engine. Three ways to integrate it.
For equipment manufacturers and system integrators. Scope, hardware support and pricing are defined for each project.
Embedded
readout
Add a selected, bounded function to your MCU-based product. Define the memory, timing and input contract around your firmware.
Local
intelligence
Run richer learning and decision workflows on an industrial gateway, close to your equipment and local data.
Engineering
toolkit
Build and qualify device-specific models with your team. Compare against your current solution before choosing a deployment.
Your device.New capabilities.
Tell us what your device should learn, detect or decide.
Let’s define a measurable pilot.