Industrial Edge Intelligence

Edge Intelligence
Run Apps, Analytics, and AI at the Edge
Make decisions where data is generated, with lower latency and greater operational resilience.

95 global sites deployed in 18 weeks

When decisions depend on the cloud, operations slow down
Industrial environments can’t rely on centralized systems for every decision. Latency, bandwidth constraints, and intermittent connectivity introduce delays and risk when data must leave the process before action can happen.

Without local execution, analytics lag behind events, AI can’t respond in real time, and operations become dependent on external infrastructure. Edge Intelligence brings compute, analytics, and AI closer to machines so data can be processed, analyzed, and acted on where it’s generated.

The execution layer of the industrial data foundation
Edge Intelligence turns structured data into action. By running applications, analytics, and AI at the edge, it enables faster decisions, improves operational resilience, and reduces dependency on centralized systems so industrial environments can operate in real time.

Proven at scale across industrial environments
From multi-site deployments to measurable operational gains, Litmus helps manufacturers turn fragmented data into scalable execution.

95 sites deployed in 18 weeks
standardized industrial data architecture
$3M/month savings
optimized packing and volume tracking
126 edge deployments
standardized industrial data architecture
Reduced plant downtime
Real-time monitoring and corrective action

Edge intelligence capabilities
Run applications, analytics, and AI at the edge so industrial data can drive immediate action across operations.

Edge Applications
Deploy and scale edge applications where they create value
Applications are most effective when they run close to machines and users. Edge applications provide a local runtime for processing, storing, analyzing, and visualizing data without relying on centralized systems.

What this enables:

Deploy containerized applications at the edge

Support low-latency processing and local execution

Standardize application deployment across sites

Run operational, analytical, and visualization workloads locally
Edge Analytics
Analyze and act on data in real time
Edge analytics enables KPIs, anomaly detection, and condition-based actions to run in real time—without sending every signal to the cloud.

What this enables:

Compute KPIs at the source of data generation

Detect anomalies and deviations in real time

Trigger actions immediately based on analytical outcomes

Reduce cloud bandwidth dependency for high-frequency data
Edge AI / ML
Deliver predictions and optimization without delay
AI models create more value when they run where decisions are made. Edge AI enables local inference for anomaly detection, forecasting, optimization, and classification.

What this enables:

Run machine learning inference locally

Deliver immediate predictions and optimization signals

Extend enterprise AI through distributed edge execution

Keep sensitive data closer to the source
Edge LLM / SLM
Enable natural-language interaction with industrial systems
Language models make industrial systems easier to interpret by summarizing events, explaining conditions, and enabling natural-language workflows.

What this enables:

Summarize events and operational conditions

Interpret logs and system activity

Support guided, context-aware assistance

Enable natural-language workflows at the edge
Agentic Edge
Move from automation to intelligent action
Agentic Edge introduces guided autonomy—allowing software agents to observe conditions, reason over data, recommend actions, and execute workflows within defined guardrails.

What this enables:

Observe and interpret industrial conditions in real time

Reason across OT and IT data

Recommend and execute next-best actions

Improve consistency in troubleshooting and workflows

Why edge intelligence matters

A strong edge intelligence layer enables:

Faster response to industrial events
Reduced latency between insight and action
Greater resilience in offline or constrained environments
Real-time analytics and AI-driven optimization
More accessible insights through language-based workflows
A scalable execution layer for Industrial AI

Built for legacy and modern industrial systems
Litmus integrates with the industrial stack you already rely on, including PLCs, SCADA platforms, historians, MES, cloud infrastructure, and analytics tools.

FAQs
Quick answers to your industrial data questions.

Execute Industrial AI where it matters most
Run models, analytics, and applications at the edge to enable real-time decisions across operations.

Run Apps, Analytics, and AI at the Edge

95 global sites deployed in 18 weeks

When decisions depend on the cloud, operations slow down

The execution layer of the industrial data foundation

Proven at scale across industrial environments

95 sites deployed in 18 weeks

$3M/month savings

126 edge deployments

Reduced plant downtime

Edge intelligence capabilities

Deploy and scale edge applications where they create value

Analyze and act on data in real time

Deliver predictions and optimization without delay

Enable natural-language interaction with industrial systems

Move from automation to intelligent action

Why edge intelligence matters

Built for legacy and modern industrial systems

FAQs

What is Edge Intelligence?

Why run applications at the edge?

How does edge analytics improve industrial operations?

What is the role of Edge AI and machine learning?

How do language models support edge intelligence?

What is Agentic Edge?

Execute Industrial AI where it matters most