Open models
10 articles
Enterprise AIA Corporate AI Strategy for 2026: From Pilots to Production
Most enterprises use AI; few run it at scale. A practical framework for moving from pilots to production, with a clear answer to the question pilots skip: where the inference capacity comes from.
5 min read
Model routingBuild, rent or network? Sourcing AI inference in 2026
CTOs now have three ways to source AI inference: build on their own hardware, rent from a cloud or model API, or buy from an open network of independent providers. This guide compares them on the criteria that decide the outcome: demand shape, model choice, jurisdiction, verification and exit.
5 min read
SecuritySecuring the AI Model Supply Chain, From Weights to Serving
A model file is executable risk: it can carry code, be swapped in transit or be served by a machine that is not what it claims. A layered control set for model provenance, safe formats, signed releases and attested serving.
5 min read
Distributed trainingDistributed Training Across Clusters: What Works Over the WAN Today
Low-communication training has moved from paper to practice, with models trained across continents and among peers who come and go. What the research shows, what still binds, and where an open network of verifiable machines helps.
4 min read
Generative mediaGenerative Media Pipelines: Right Hardware, Pay Per Result
Image, video and audio generation have cost profiles unlike chat. How to route each job to hardware that fits it, meter it in units that match the work, check licence territory and mark outputs for provenance.
5 min read
Inference optimizationInference Optimisation From Consumer GPUs to the Data Centre
Quantisation, speculative decoding, continuous batching, paged and reused KV cache, and prefill/decode disaggregation: what the 2025-2026 work shows, and what each technique means when the GPUs belong to many operators on a wide-area network.
6 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
Open modelsOpen models need open infrastructure: provenance and licences
Once open weights are released, the builder loses sight of how they are served. This article covers what model builders should expect from the infrastructure that serves their work: proof of which weights ran, licence terms enforced in the serving path, gated access that holds, and attribution that reaches the user.
5 min read
Public sectorPublic Sector AI: Buying Capability Without Buying Lock-In
Governments in the US, UK and EU now tell agencies to avoid AI vendor lock-in, protect government data from commercial training and assess impacts before deployment. A procurement checklist that turns those policies into contract terms and architecture.
4 min read
RetrievalRetrieval at the Source: Embeddings and Search Near the Data
Retrieval pipelines copy an organisation's documents into embeddings, indexes and caches, often far from where the data lives. Why embeddings are sensitive data, how to size them, and an architecture that keeps retrieval close to the source.
4 min read