CORE PLATFORM
IoT & Edge Computing
Sensor to decision, without the cloud round-trip.
Not every intelligent system can afford the latency of a round-trip to the cloud. IoT & Edge Computing is how we run inference at the point of action - retrofitting legacy equipment with modern sensors, running AI models on industrial gateways, and bridging protocols across decades of plant-floor technology.
We design edge architectures that are resilient, secure, and maintainable at scale - from a single pilot machine to a fleet of thousands across multiple sites. Every deployment includes OTA update capability, remote monitoring, and graceful degradation when connectivity drops.
Our edge practice is built on the reality that most industrial environments are brownfield: the equipment is old, the protocols are mixed, and the network is unreliable. We design for that world, not the greenfield fantasy.
Capabilities
Sensor Retrofit
Adding vibration, thermal, acoustic, and vision sensors to legacy machines - giving old equipment new intelligence.
Edge Inference
ML models running on ARM / NVIDIA Jetson / industrial gateways - millisecond decisions where the data lives.
Protocol Conversion
Modbus, Profinet, EtherCAT to OPC UA / MQTT / REST - unifying decades of industrial protocols into a modern data layer.
Device Fleet Management
OTA updates, remote monitoring, lifecycle orchestration - managing thousands of edge devices from a single pane.
Low-Latency Processing
Deterministic response times for safety-critical loops - when milliseconds matter, the cloud is too far away.
Offline / Intermittent Operation
Resilience to network outages - edge nodes that keep running, buffering, and syncing when connectivity returns.
Technical Stack
Common questions
Why run AI at the edge instead of in the cloud?
Because not every intelligent system can afford the latency of a cloud round-trip. For safety-critical loops that need deterministic, millisecond response times, we run inference at the point of action - on ARM boards, NVIDIA Jetson or industrial gateways - where the data lives.
Our machines are old and have no sensors - can they still become intelligent?
Yes. Sensor retrofit is a core capability: we add vibration, thermal, acoustic and vision sensors to legacy machines and convert plant-floor protocols such as Modbus, Profinet and EtherCAT to OPC UA, MQTT or REST - giving old equipment new intelligence.
What happens when the network drops?
The system keeps running. We design edge nodes for offline and intermittent operation: they continue processing, buffer results and synchronise when connectivity returns - graceful degradation is part of every deployment.
Can Tavlo manage edge devices at fleet scale?
Yes - from a single pilot machine to thousands of devices across multiple sites, with over-the-air updates, remote monitoring and lifecycle orchestration from a single pane, on stacks such as Azure IoT Edge and AWS IoT Greengrass.
How do we start a project with Tavlo?
Write to contact@tavlo.tech and describe the process or line you want to improve. We respond within two business days and typically start with a 30-minute call. There is no public price list - engagements begin with a conversation, and implementation details are shared under NDA.
Your next intelligent system starts here.
Whether you're in DACH or beyond, we're ready to deliver.