Why SymphonyAI

Discover operational excellence at scale with SymphonyAI’s trusted predictive and generative AI applications for industry.

2-4%

Increase in product throughput

20-50%

Reduction in unplanned downtime

3-5%

Increase in energy efficiency

Intelligent Software for Industry 4.0

Solve core challenges and efficiently scale and standardize processes across sources. With 30+ years in the industrial and manufacturing sectors, SymphonyAI deeply understands your unique data challenges. Leveraging this strong domain expertise, SymphonyAI builds solutions that ensure rapid returns and deliver tangible value with initial deployment times in 4 – 12 weeks.

Experts in Industry 4.0

Value-based approach
Start small, scale fast
Domain expertise
AI capabilities
Composable deployment

Industrial AI software applications expertly designed by technical professionals who understand the challenges of industry and manufacturing. Delivering valuable domain-specific products and solutions, with pre-built solutions to advance and enhance workflows in manufacturing and industry.

See how our customers are realizing value.

Collage of screenshots showing industrial data monitoring and analytics software interfaces including line graphs, anomaly trend plots, machine learning preprocessing pipeline, plant copilot chat with efficiency graph, health score dashboard, and connectivity logos for OPC UA, AspenTech, InfluxDB, Modbus, OSIsoft, ODBC, Kafka, Microsoft Azure, and Amazon Kinesis.

Within just 8 weeks, SymphonyAI’s suite of standard, scalable, and composable apps tackles core industrial challenges, unlocking immediate value from enterprise data.

Reuse data and models to quickly create new applications on the IRIS Foundry Platform – a standardized, scalable data management tool that enables faster access to contextualized industrial data across multiple sites throughout an enterprise for business applications and use cases.

Flow diagram showing integration of conventional, operational, and engineering data into data contextualization connected to a knowledge graph, pre-trained industrial LLM, and predictive models, which interface with an industrial machine display and an API.

Deploy enterprise-specific data and use cases faster with industrial-specific libraries of asset templates, definitions, and failure modes. And with this standardized and contextualized data, a comprehensive KPI library instantly creates previously unattainable data insights.

The complete process is powered by orchestrated enterprise data and pre-built industrial data connectors in a unified namespace.

Circular diagram with a blue center labeled 'Unified Namespace' surrounded by eight labeled icons representing Industrial components: Machine, Maintenance, Product, ERP, Process, MES, P&ID, CRM, and Inventory.

Enhance and add value to data operations through innovative features and tools. SymphonyAI’s role-based AI copilots provide an intuitive way to explore data insights and metrics previously undiscoverable with traditional data systems and user interfaces.

Other tools and features like P&ID ingestion, data contextualization, and predictive modeling add layers of built-in intelligent logic for smarter data input, processing, and decision-making.

Future predictions from enterprise data are unlocked, such as growth rates, potential maintenance or downtimes, staffing, and other business outlooks.

Screenshot of an AI-driven insights companion interface for boiler maintenance analysis showing user queries and AI responses including a forecast graph and efficiency trends for heat transfer in two boilers, with recommendations for cleaning and measures to avoid efficiency degradation.

Work with your existing partners and easily achieve seamless deployments that integrate with your existing ecosystem, including all data sources available on-premises, through private cloud services, or hosted SaaS.

Developed on Microsoft Azure, IRIS Foundry enhances SymphonyAI’s partnership with Microsoft by merging IT and OT data on an enterprise scale through Microsoft Fabric and employs Azure OpenAI Service to empower manufacturers with role-based copilots for rapid identification and resolution of operational challenges.

Circular infographic showing IRIS at the center, surrounded by concentric rings labeled 'Protocols' and 'Datasources.' The Protocols ring includes MQTT, ODBC, Kafka, EtherNet/IP, SMTP, MSMQ, SFTP, REST API, HTTP, XML, and CAN. The outer Datasources ring features logos and names of companies and platforms, including Tulip, PLEX, ABB, EH, Honeywell, Yokogawa, InfluxDB, Siemens, GE, Wonderware, Emerson, Schneider Electric, Canary, IBM Maximo, Databases, SAP S/4 HANA, Mitsubishi Electric, Amazon S3, IBA, OSIsoft, Omron, Aspentech, and Azure Data Lake. The image illustrates connectivity and integration capabilities of IRIS with various industrial protocols and data sources.