Edge AI
11 articles
Distributed computingThe Tenzro testnet is live
The Tenzro testnet started today: a network for compute of every kind, where AI inference, compute, storage and data are served by machines that each prove who they are with a hardware key, and settled on one network. Here is what is running, how to install a node and how to join.
2 min read- Edge AI
Compute that stays local: running your own Tenzro node
What a node on your own hardware is, what it runs, what the documentation says it needs, and how its keys stay in the machine. Documented requirements only: no measured running costs have been published yet.
4 min read 
Edge AIAgentic Harnesses on Small Devices: Orchestrating From the Edge
Most of an agent's work is orchestration, not large-model inference. Why the harness belongs on small hardware near the data, what runs on a Tenzro edge node today, and what edge harness hosting will add once it ships.
5 min read
ManufacturingAI on the Factory Floor: Edge Inference and Machine Identity
Factories need AI that keeps running when the internet does not, on machines that can prove what they are. How to place inference on the shop floor, anchor every device in hardware, and meet the security regimes now arriving for industrial products.
4 min read
Computer visionComputer Vision at the Edge: Infer Locally, Escalate Rarely
Cameras produce far more pixels than anyone should ship to a data center. A tiered architecture for vision AI: small detectors at the camera or gateway, larger models only for the frames that need them, and privacy built into the split.
4 min read
Hardware identityDevices that join a network at first boot, with hardware identity
For hardware manufacturers, the identity a device carries out of the factory decides what it can do in the field. This article covers which identifiers can anchor a machine and which cannot, why keys belong sealed to the hardware, and how devices can join an open AI network from the first time they power on.
6 min read
Hardware identityHardware-Rooted Identity for Machines: TPMs, Enclaves and Passkeys
A key file can be copied, and a copied key is a second machine nobody knows about. Why Tenzro derives every machine and person's identity from keys that never leave hardware, and how that works on servers, laptops and boards without a TPM.
5 min read
Model routingModel Ladders: Answer With Small Models, Escalate Only When Needed
Most requests do not need the largest model. What the research on cascades and routing actually shows, where it falls short, and how Tenzro routes by measured difficulty and closes the loop on escalation.
5 min read
Edge AIOne Codebase From a Single-Board Computer to a Rack
Tenzro builds one node for every class of machine, from a Raspberry Pi to a GPU server, by varying compiled features and resource presets rather than forking the code. How the tiers work, what we measured, and why small devices belong in an AI network.
5 min read
Physical AIPhysical AI: Robots That Buy Compute and Sell Their Work
Robots and field devices increasingly need inference they cannot run on board, and produce data and work others will pay for. What it takes for a machine to transact safely: identity, budgets, placement and verifiable evidence.
5 min read
Telco edgeTelcos as AI edge clouds: inference inside the latency budget
Telecom operators have the sites, the fibre, the licenses and the customer relationships that low-latency AI needs. This article covers how to split an inference request across device, edge and regional GPU, what a latency budget actually allows, and what a telco needs in order to sell edge inference to buyers it has never met.
5 min read