Proof
Explore real deployments, case studies, and published research showing how AnyLog makes data across machines, plants, and sites accessible as one logical system.
Field
3 sites. 1,000 sensors. AnyLog replaces point-to-point integration and manual configuration with an automated, distributed approach. Data is captured through existing or custom southbound APIs, then exposed to AI, applications, and users as one logical system — while data remains physically distributed.
A smaller municipal team monitors water, wastewater, and power on an EdgeLake fabric, with alerts and AI at the edge.
AnotherTrail / AnotherPeak: onboard AI and decentralized SQL across an electric passenger fleet with no cloud dependency.
Self-learning heating control across buildings on EdgeLake, with federated AI and full data sovereignty.
Deploy AnyLog as peer software: agents land on plants, cities, and sites, then form one queryable lake. Data stays put; the network answers as a single system — including Open Horizon rollouts.
Product documents
One-pager on AnyLog Edge Data Fabric — architecture, value, and where it lands in an industrial stack.
Product overview of the fabric: unified namespace, query paths, and how data stays at the source.
Agent- and edge-based platform that presents distributed data, assets, compute, and services as one logical system.
Research
Moshe Shadmon, Daniel J. Abadi, Owen Arden, and Faisal Nawab. The founding vision for a decentralized platform to publish and query structured IoT data.
Moshe Shadmon and Faisal Nawab. What it takes to virtualize data and resources across a live worldwide edge.
Faisal Nawab on unifying IoT data processing without collapsing it into a single warehouse.
Why AI and IoT stall without a way to manage distributed data — and how a fabric fills that gap.
