Sensor-data feature engineering
Fuse load type, altitude, timing, and equipment telemetry into activity classifications.
USE CASE · Computer vision
ML on the sensor and image data your equipment is already producing.
Activity recognition, equipment attribution and quality monitoring, built from real telemetry and deployed into your existing operational stack.
Built with your teamYour data. Your infrastructure.
Sensor + altitude + load type
Multi-signal feature engineering for activity attribution (Versatile)
Challenge → Solution
What's broken, and what we do about it.
This is your problem
This is our solution
Problem
Your equipment generates rich sensor data, but you have no way to attribute usage to specific tasks, operators, or subcontractors.
Our solution
Multi-signal ML that fuses sensor patterns (load type, altitude, timing, …) into activity classifications. (Versatile)
Problem
Off-the-shelf computer-vision SaaS can’t handle the specifics of your operational environment.
Our solution
Custom pipelines trained on your data, deployable on your infra.
Problem
You have prototypes that work in a notebook but never make it into the operations team’s daily tooling.
Our solution
We deliver in-stack, into the systems your ops team already uses.
Capabilities
Vision and sensor ML for operations.
Built from your real telemetry — not a generic model fine-tuned on a public dataset that doesn’t look like your environment.
Operational ML for sensor + image data
The Versatile pattern: multi-signal feature engineering, custom pipelines, in-stack delivery.
Image / video classification at scale
Custom-trained models for the visual specifics of your operational environment.
Multi-signal fusion
When neither sensor data nor imagery alone is enough, we combine signals into a single decision layer.
Edge / on-site inference
Deploy where the data is produced, with graceful degradation when network connectivity drops.
Integration into existing dashboards
Outputs land in the systems your ops team already uses — not a new SaaS portal to ignore.
Engagements
How we deliver computer vision.
Rapid-Impact Intervention
SWAT Team
A high-impact strike team that diagnoses, architects, and ships. We bring the ML engineers, infra, and domain expertise needed to deliver measurable lift within weeks.
- End-to-end diagnostic and solution delivery
- Cross-functional team: ML engineers, infra, domain SMEs
- Measurable KPI improvement with defined timelines
Applied Research Partnership
The ML Lab
A dedicated research partnership where we co-develop proprietary models alongside your team — from initial hypothesis through production deployment.
- Joint model development and full knowledge transfer
- Custom algorithms built on your data and objectives
- Structured engagement from discovery to production scale
Risk-Free Experimentation
Simulator
A controlled experimentation environment for validating strategies before they touch production. Test against realistic system dynamics and quantify impact upfront.
- Realistic simulation with historical data replay
- A/B scenario testing for system-level decisions
- Quantified impact forecasting before production rollout
Proof
Computer vision in operational environments.
Ready to build?
No pitch decks, no generic demos — just a technical conversation about your data and your goals.