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Robotics & Automation

Control systems and automation software for hardware-integrated products, from sensor to interface.

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Overview

What this solves

Robotics and automation software sits at an uncomfortable intersection: it has to work with the actual physical constraints of the hardware — timing, sensor noise, failure modes — while still being software an operator can trust and a team can maintain. A lot of automation software gets built by people who understand one side of that and not the other: hardware engineers who write software as an afterthought, or software teams who treat the hardware as a black box that always behaves the way the datasheet says it will. We build control systems and automation pipelines with both in mind: aware of the hardware's real behavior, and built with the same engineering discipline as any other production software.

In practice that means designing for the failure cases first — a sensor that reports noisy or missing data, a control loop that needs to fail safe rather than fail silent, an operator who needs to understand what the system is doing and why, not just watch a green light. Automation software that only works when everything goes right isn't automation, it's a demo. The systems we build are meant to be trusted on the day something goes wrong, not just on the day of the walkthrough.

Capabilities

What we build

Control system software

Software layers that sit between hardware and operator, translating sensor input into control decisions and status an operator can act on.

Automation pipelines

End-to-end automation of processes that were previously manual or semi-manual, built around the actual constraints of the hardware involved.

Sensor integration

Ingesting and making sense of sensor data — the unglamorous but critical layer underneath any automation system.

Operator interfaces

Dashboards and control interfaces built for the people actually running the system day to day, not just for a demo.

Fail-safe design

Control logic that fails safe rather than fails silent — a sensor dropout or fault state is surfaced to the operator immediately, not masked until something breaks downstream.

Tech Stack

Built on infrastructure made for real-time data

MQTT

Lightweight messaging between sensors, controllers, and the software layer above them.

AWS Lambda

Event-driven processing for automation logic that scales with system size.

WebSockets

Real-time status and control data pushed to operator dashboards.

DynamoDB / SQS / SNS

The same durable, event-driven data infrastructure used across our real-time systems work.

Who This Is For

Built for teams already in motion

Hardware & robotics product teams

Building the software layer for a robotics or automation product and need it to actually reflect the hardware's real behavior.

Industrial operations

Automating processes that are currently manual or semi-manual, with real sensor and control constraints.

Teams with hardware but no software team

The hardware works — the software around it is the missing piece.

This is the same real-time, hardware-aware engineering discipline behind our drone and live-tracking work, applied to robotics and industrial automation — because underneath the specifics, it's the same problem: get real data out of hardware and put a person or a system in a position to act on it.

A good sign that a project needs this kind of software work rather than more hardware: the hardware already does what it's supposed to, but nobody trusts the software layer around it enough to fully automate the process, so a person is still manually checking or overriding it. That gap between working hardware and trusted software is exactly where this department operates.

FAQ

Common questions

Do you build software for existing robotics/automation hardware, or only new products?
Both — most engagements are the software layer for hardware that already exists and works, not a from-scratch hardware+software build.
What kind of hardware have you worked with?
Sensor and control systems across automation, robotics, and drone hardware — the underlying software patterns carry across, even when the specific hardware differs.
Can this integrate with our existing operator dashboards or does it replace them?
Depends on what exists — we can extend an existing interface or build a new one, based on what's actually there.
How do you handle sensor data that's noisy or unreliable?
By designing for it upfront rather than assuming clean input — filtering, validation, and fail-safe defaults built into the pipeline, so a bad sensor reading degrades gracefully instead of producing a confident wrong answer.
Do you need physical access to the hardware to build this software?
Not always — a lot of the work is done against documented sensor/control interfaces and simulated data, with on-site testing at key milestones rather than continuous physical access.
Can this reduce how much manual monitoring our team needs to do?
That's usually the actual goal — automating the monitoring and decision-making that's currently done manually, with alerting as a safety net rather than a replacement for the automation itself.

Have a project in mind?

Tell us what you're building, and we'll scope the software around it.

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