IRIS Flows

Agents that don’t just recommend—they act

Industrial operations generate more decisions per minute than any team can handle manually. IRIS Flows puts autonomous AI agents to work in your processes—analyzing events, coordinating responses, and executing actions across assets, teams, and facilities in real time. Built on SymphonyAI’s Industrial LLM with 300+ pre-built agents and three modes of governed autonomy, it’s the only agentic AI platform engineered for the complexity of industrial operations.

Agentic AI, proven in production

300+


Pre-built industrial agents. Ready to deploy across manufacturing, energy, and process operations—no build time required.

15%


Reduction in unplanned downtime. Measured outcome across IRIS Flows deployments in smart factory environments.

IRIS Flows agentic workflow canvas showing a multi-step automation sequence from Start through nodes for Get Impact Factor of KPI, Generate Graph, Get RCA node…IRIS Flows agentic workflow canvas showing a multi-step automation sequence from Start through nodes for Get Impact Factor of KPI, Generate Graph, Get RCA nodes, Summarize Channel data, and Generate PDF to End

Your operations are too complex for if-then logic

Rule-based systems handle predictable scenarios. Industrial operations aren’t predictable. Equipment behaves differently under different conditions, shifts, and loads—and the interactions between assets, processes, and teams create complexity that static rules can’t navigate. IRIS Flows agents reason from context, not rules. They understand what’s happening, evaluate options, coordinate with other agents and with people, and take action—adapting as conditions change.

AI advises. Humans decide.

Agents surface insights, flag anomalies, and recommend actions. Your team reviews and approves every decision. Full visibility, zero autonomy risk. Start here.

AI acts. Humans stay in the loop.

Agents execute defined task classes autonomously—escalating edge cases to human experts. Speed increases. Risk stays managed. Expand agent scope as confidence builds.

AI runs the workflow end to end.

Agents sense, decide, and act across full process loops—continuously optimizing without manual triggers. Human oversight is available but not required for routine operations.

Deploy

Choose from 300+ pre-built agents or design custom agents visually or with natural language—no code required. Agents understand your domain from day one, built on the Industrial LLM.

Connect

Agents plug directly into IRIS Foundry’s unified data layer—accessing real-time sensor data, historian records, maintenance logs, work orders, and enterprise systems simultaneously.

Orchestrate

Multi-agent workflows form dynamically. When a KPI deviation fires, a root cause agent investigates, a scenario agent models outcomes, and a coordination agent routes the right action to the right person or system.

Scale

Multi-agent workflows form dynamically. When a KPI deviation fires, a root cause agent investigates, a scenario agent models outcomes, and a coordination agent routes the right action to the right person or system.

300+ agents. Every critical operation covered.

Pre-built agents are production-ready across the highest-impact use cases in industrial operations

Alarm management and RCA

Intelligent alarm responders triage alerts in real time—filtering noise, identifying root causes, and routing actions to the right operator or system before issues escalate.

Predictive maintenance

Maintenance coordinator agents connect asset health scores from Predictive Asset Intelligence to work order systems—automatically scheduling interventions based on failure probability and operational priority.

Shift intelligence

Shift handover agents capture and contextualize operational events, KPI deviations, and open actions—so every shift starts with a complete, accurate picture of plant status.

Process optimization

Optimization planner agents continuously analyze process conditions, model alternative setpoints, and recommend or execute adjustments to maximize yield, throughput, or energy efficiency.

Safety and compliance

Agents monitor safety-critical conditions, trigger permit-to-work workflows, and coordinate inspection and compliance actions across connected worker systems—maintaining audit trails automatically.

Custom agent creation

Build domain-specific agents using a visual designer or natural language. Agents inherit the Industrial LLM’s contextual understanding of your assets, processes, and data—no training data preparation required.

Agents that run on industrial-grade intelligence

IRIS Flows multi-agent orchestration diagram showing a KPI deviation triggering a coordinated sequence of root cause, scenario modeling, and expert review agen…IRIS Flows multi-agent orchestration diagram showing a KPI deviation triggering a coordinated sequence of root cause, scenario modeling, and expert review agents working across a connected workflow

IRIS Flows agents aren’t running on generic AI. Every agent is powered by SymphonyAI’s Industrial LLM—trained on 7+ trillion industrial data points including sensor readings, maintenance records, work orders, and engineering documentation. Agents understand the language, failure modes, and operational logic of your industry before they ever connect to your plant.

Because IRIS Flows sits on IRIS Foundry, agents have access to a fully unified, contextualized data foundation—not isolated data streams. The result is agents that reason with complete situational awareness: real-time OT data, historical trends, asset hierarchies, P&IDs, and enterprise system context, all in one coherent intelligence layer.

Purpose-built agents for every industrial domain

Nine named domain agents, engineered for the specific processes, data types, and decision contexts of each operation

Manufacturing Digital Twin Agent — Teams and M365

Integrates with Microsoft Teams and M365 Copilot via MCP. Plant engineers and managers query asset status, maintenance history, and performance trends in natural language—directly from their existing Microsoft workflow.

Oil and Gas Operations Agent

Monitors upstream and midstream assets, detects process deviations, and coordinates maintenance and safety workflows. Integrates with existing DCS, SCADA, and historian infrastructure without replacement.

Intelligent Factory Agent

Continuously optimizes production across assembly, discrete manufacturing, and mixed operations—coordinating OEE improvement, quality control workflows, and shift intelligence in a single agent loop.

Industrial Data Exploration and Investigation Agent

Empowers engineers and analysts with AI-powered search, root cause analytics, and anomaly detection across vast, complex OT/IT data landscapes.

Smart Utilities Agent

Optimizes energy utility operations with AI-driven forecasting, grid management, and automated trading to enhance efficiency, reliability, and sustainability.

Warranty Claims Agent

Streamlines warranty claims for manufacturers and dealers, leveraging unified data and AI to detect fraud, automate workflows, and improve product quality at scale.

Manufacturing Digital Twin Agent

Unlocks real-time visibility and advanced analytics for manufacturing operations by creating dynamic digital twins of assets, lines, and plants, connecting seamlessly to IRIS Foundry and Azure for scalable insights.

Frontline Worker Agent

Empowers front-line teams with context-driven guidance, automated SOPs, and instant access to expert support, ensuring safety and operational agility at the point of work.

Energy Generation & Distribution Optimization Agent

Enables real-time orchestration and predictive optimization of power generation and distribution, integrating renewables and conventional sources for grid resilience.

Why IRIS Flows, not a generic AI agent platform

IRIS Flows Create Workflow dialog showing a three-step setup process with Agentic Workflow type selected and a project list including Botting Error Filtering, Industrial Demo Agents, and Flow Development Project

Generic AI agent platforms require extensive setup, custom training, and months of integration work before they understand your operation. IRIS Flows arrives pre-trained on industrial data—with an agent library, domain-specific ontologies, and a data foundation already built. Your team deploys agents in days, not quarters.

 

Building your own agentic AI in-house means owning the training data, the integration work, the governance framework, and the ongoing model maintenance—indefinitely. IRIS Flows delivers pre-built depth, governed autonomy controls, and continuous model improvements maintained by SymphonyAI’s industrial AI team.

 

Common Questions

What industrial teams ask before deploying IRIS Flows

Do we need IRIS Foundry to use IRIS Flows?
Yes. IRIS Foundry is the data foundation that IRIS Flows agents operate on—it provides the unified, contextualized data layer that gives agents situational awareness across your operation. If you’re not on IRIS Foundry yet, that’s where we start.
Most customers activate their first pre-built agent within days of connecting IRIS Foundry to their data sources. Custom agent design using natural language or the visual builder typically adds days, not weeks. Complex multi-agent workflows are deployed iteratively, starting with the highest-impact use case.
Every agent operates in one of three modes: Assistive (recommends, humans decide), Augmented (acts on defined task classes, escalates edge cases), or Autonomous (full execution loop, human oversight available). Autonomy mode is set per agent, per workflow—and can be adjusted at any time from the central governance console.
Yes. Agents access data through IRIS Foundry’s 100+ pre-built connectors—covering historians, DCS, SCADA, ERP, CMMS, and IoT sources. They can also write back to connected systems: triggering work orders in SAP, updating CMMS records, or sending alerts through Microsoft Teams via MCP integration.
A copilot surfaces information and suggests actions. IRIS Flows agents execute actions—autonomously if configured to do so, or with human approval at defined checkpoints. Multi-agent orchestration means they also coordinate with each other: one agent’s output becomes another’s input, forming end-to-end process automation, not just point-in-time recommendations.