CNC cell · OPC-UA
Node live
AnyLog EDF
Manufacturing · Smart cities · Utilities · Green energy · Maritime
Give AI unified access to operational data — without moving it
AnyLog is a distributed edge data platform that provides real-time access to operational data and metadata wherever it is created or stored — across machines, devices, systems, plants, sites, and edge units — as one unified system.
Data remains at the source, while AI agents and applications access and reason across the entire distributed environment without the need to centralize data.
Distributed Queries
Distributed UNS
Edge Knowledge Graph
SQL + MCP
No Cloud
Days to deploy
How it works
One data layer across machines, plants, and sites.
Deployed on your infrastructure.
Deploy nodes at the plants and query the fabric as one system. Nodes run inside your firewall over authenticated, encrypted peer-to-peer connections; live OT data stays at the source, with no central copy and no cloud hop.
12,840 South · Line 3
8,420 North · Line 1
21,260 Σ lines
- Capper torque high on Line 3
- Case pack lag vs capped bottles
- North Line 1 rate recovered
Time to value
Deployment measured in days
Move from one use case to a scalable, multi-site deployment through four simple steps.
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01
Deploy AnyLog
Run AnyLog agents on existing edge devices and servers. Data is stored and processed locally.
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02
Connect your data
Use AnyLog’s southbound connectors for PLCs, sensors, MQTT brokers, historians, databases, and APIs.
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03
Define the UNS logically
Define any number of logical namespaces by asset, location, or relationship—without routing or centralizing the data through a broker.
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04
Scale horizontally across sites
Repeat Step 1 to expand. Each new node joins the same logical system without rebuilding applications or central pipelines.
Knowledge graph
Bring the Knowledge Graph to the production floor
AnyLog combines a Unified Namespace (UNS) with a Distributed Knowledge Graph, so applications and AI understand not only the values, but how assets, processes, locations, and systems relate to each other.
A live Knowledge Graph across your production environment
Same distributed operational data
PLCs · historians · MQTT · edge stores — still at the source
Multiple UNS views, same stores
Production UNS
Maintenance UNS
Energy UNS
Quality UNS
Manufacturer UNS
Management UNS
Knowledge Graph
Map the relationships between assets, processes, locations, and systems, while the underlying data stays in place.
Aggregate in place, then choose the view
Sum bottles capped on each line and cases ready to ship across plants — one query, no warehouse copy.
Use the knowledge graph and the UNS to define different views of that same data: by line, plant, process, or role.
Who uses it
AI agents
Applications
Operators
Management
Rules Engines
Compliance
Markets we serve
Built for operations that shouldn’t depend on the cloud.
One APIfor every machine, site, and database
UNSauto-generated from connected sources
Knowledge Graphlive across machines, lines, and sites
MCPnatural-language queries on live edge data
Daysto a live first use case on the floor
Capabilities
One operational data layer across your edge. Data stays in place.
Unified real-time data
Virtualize distributed sources into one view. Process and analyze at the edge instead of waiting on a warehouse.
Edge AI & agentic workflows
Make OT data locally accessible to models and agents. MCP exposes live industrial context to LLMs without a data lake.
Ownership & sovereignty
Physical data stays under your control. Reduce cloud egress, keep IP on-prem, and satisfy plant-level compliance.
Resilient operations
Replication, a rules engine, and policy-based management keep lines running when the WAN does not.
IoT connectors & APIs
REST, pub/sub, databases, and industrial connectors — one software stack instead of a pile of proprietary projects.
Single-system resources
Monitor and govern distributed nodes like one system, with real-time telemetry and policy-driven controls.
Watch
See the fabric, not just the architecture diagram.
AnyLog Explained
Why distributed operational data needs a fabric — and what AnyLog changes.
SQL through a single system image
Monitor distributed infrastructure and run SQL as if the edge were one system.
Unified Namespace and knowledge graph
A unified namespace and knowledge graph without a central broker.
A complete view for AI agents
How AnyLog gives AI agents a complete view of distributed infrastructure.
Sabetha product demo
A live walkthrough of AnyLog in the field, including the Sabetha deployment.
Proof, not slides
Field stories from production environments.
Sabetha, Kansas
A smaller municipal team replaced aging SCADA/historian stacks with an EdgeLake fabric for water, wastewater, and power.
Secure OT with Dynics
PLC, HMI, and historian data published into a unified namespace — virtualized for live AI, still local to the plant.
Federated heating, VÖFAB
WINNIIO runs self-learning building control across sites on EdgeLake, with full data sovereignty.
Technical FAQ
How the fabric works — for applications, AI, and operators.
What is AnyLog?
AnyLog is a decentralized edge data platform made up of software agents that run on devices and servers near industrial, IoT, and OT data sources. The agents connect to sensors, PLCs, historians, and databases, then make data across machines and sites accessible through one API and any number of logical Unified Namespaces. Applications and AI see one queryable system while the raw data remains at the edge.
Does operational data leave my network?
No. Nodes run next to the machines, typically inside your firewall. There is no requirement to copy raw telemetry to a cloud data lake. Queries return answers; the data stays on-prem.
How does AnyLog keep OT data secure?
AnyLog nodes can run inside your firewall, keeping data at its source. Nodes communicate through authenticated, encrypted peer-to-peer connections, and each node enforces its own access policies. Applications receive only the query results they are authorized to see, while the underlying data remains under your control.
Who owns the data in an AnyLog deployment?
You do. AnyLog runs in your infrastructure; it is not a SaaS service that hosts or owns your data. Each node enforces access policies locally, so only authorized users, partners, applications, and AI agents can query the data and receive the results their permissions allow.
How do applications and AI query AnyLog?
Through SQL, REST, a distributed unified namespace, an Edge Knowledge Graph, and MCP for natural-language queries by users and agents. The key idea is that AnyLog makes distributed data queryable as if it is stored in one logical system.
How is AnyLog different from a historian or a traditional UNS?
Unlike traditional historians and UNS architectures that centralize data, AnyLog uses a decentralized architecture where software nodes store and process data at the edge and share metadata peer to peer. The distributed network is accessible and queryable as one system.
Unified Namespaces are applied logically over the distributed data, without requiring data to flow through a central broker or conform to a single fixed topic structure. Multiple namespaces can be created over the same physical data and evolve with different use cases — without moving or duplicating the underlying data.
How long does a first deployment take?
Initial deployments are typically measured in days, not months. Deploy an AnyLog node on an existing edge device or server, connect it to your data sources, and define the logical Unified Namespace — without moving data through a central broker.
To expand to another machine, line, or site, simply deploy another node. It joins the same distributed, queryable system.
Next step
See the fabric on your data, not a slide deck.
Open-source via the Linux Foundation, or enterprise with HA, security, training, and support.