Specialisation · Design · Manufacture · Lifecycle
ML/AI DevOps
Model lifecycle operations for products in the field — retraining, evaluation, staged deployment and drift monitoring across your fleet.
Discuss ML/AI DevOps
Why Tekt
Models age. Fleets shouldn’t.
An on-device model is only as good as its update pipeline. We operate the loop — field data capture, curation, retraining, evaluation gates and staged OTA rollout — so accuracy improves with every release instead of decaying.
This practice extends our Lifecycle stream: the same team that manages your firmware fleet manages the models running on it.
How we deliver
Unique value, end to end
Closed learning loop
Fleet data flows back into training under privacy and consent controls.
Gated releases
No model ships without passing held-out and on-device evaluation gates.
Observable in production
Accuracy, latency and battery cost tracked per model version.
Case studies
Case studies
Real programs from this practice — the brief, the engineering approach, and where it landed.
- Case study 01 · Summit Innovations
Operating drive-thru models
ORB-iT™’s recognition models improve on a managed loop — field data curation, evaluation gates and staged rollouts keep accuracy honest as sites and conditions change.
- Case study 02 · CloudFarming
Navigation model updates
Fieldbot’s field learnings flow back into navigation improvements — versioned, benchmarked and rolled out to the fleet with rollback always ready.
- Case study 03 · Bunnings
PoC iteration at speed
The voice PoC iterated on captured real-store audio — rapid retrain-evaluate-deploy cycles that answered feasibility questions in weeks.
What we solve
Problems this practice removes
- Models decaying silently in the field
- Retraining without evaluation gates
- Fleet rollouts with no rollback
- Data collected without consent design
Tools, processes & standards
Who delivers it
The team behind it
- MLOps engineer — Registry-to-fleet pipelines on edge targets
- Data engineer — Field data curation under consent controls
- Reliability engineer — Rollout health and rollback drills
Capabilities
FAQ
Frequently asked questions
Shipped a model? Now operate it.
We keep fleet intelligence measurably improving, release after release.
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