Tuple Tech — We build connected physical products, end to end

Three layers, one team

01 Models. Custom vision and deep-learning models, trained on your data, running on your hardware.

We build: Object detection and multi-camera tracking, defect and anomaly detection, OCR on stamped and etched parts, medical and scientific image segmentation, time-series forecasting for load and yield, and classical signal processing where a neural net is the wrong tool.
The hard part: Models decay. A peer-reviewed study across 128 model/dataset pairs found temporal degradation in 91% of them1 — and in interviews with production ML engineers, not one had a principled method for deciding when to retrain2. Building the model is the short part of the job.
You get: Weights you own, an ONNX or TensorRT export that runs on the device you chose, a labelled evaluation set you can re-run yourself, and drift monitoring that tells you when the model stopped agreeing with reality.

02 Devices. Schematic, PCB, firmware, enclosure and production test — the board under the product.

We build: 4- to 8-layer mixed-signal boards, STM32 / ESP32 / i.MX / Jetson carriers, Modbus RTU and TCP, CAN and CAN-FD, BACnet/IP, LoRaWAN, NB-IoT and Wi-Fi, RS-485 sensor chains, isolated power stages, and bring-up jigs your contract manufacturer can run without calling you.
The hard part: Only 14% of IC projects now achieve first-silicon success — the lowest in over twenty years of tracking — and 75% run behind schedule3. Board-level work is not that brutal, but the lesson holds: most problems you'll call 'software bugs' turn out to be timing, power rails or optics.
You get: Gerbers, BOM with second sources, a DFM-reviewed stack-up, firmware that survives a brown-out mid-write, and a test fixture with a pass/fail light on it.

03 Systems. Cloud, fleet management, dashboards, apps and OTA — the part people actually open.

We build: Time-series ingestion and storage, MQTT and device-shadow fleet layers, staged OTA rollouts with rollback, React and Next.js dashboards, native and cross-platform mobile apps that work offline, role-based access, and APIs your other vendors can integrate against.
The hard part: Between a sensor and a number on a dashboard sit five systems — driver, firmware, transport, ingest, aggregation — and each one can make the number wrong without making it look wrong. Most of our debugging time goes into proving the number is true.
You get: Software that loads fast on a warehouse tablet, keeps working when the site loses connectivity, and is documented well enough that whoever comes after us can maintain it.

Tap any line for detail

Six sectors. The engineering underneath is the same closed loop every time — sense, decide, act, and fail safe when something breaks.

We would rather lose the enquiry than the six months.

You need fifty engineers by Monday. We are a small core with a specialist bench. If the work needs a hundred-person delivery org, a systems integrator will serve you better and we will name one.
The hard part is regulatory, not technical. We have built to IEC 61508 thinking and medical imaging standards, but we are not a notified body and we will not pretend a CE or FDA pathway is a line item.
You want the cheapest quote. We are not it. Our value shows up in the second year, when the thing is still running.
You already know exactly what to build and just need hands. Staff augmentation is a real service and there are good firms doing it. We are worse at it than they are, because we will keep asking why.