Seeq

Overview

Seeq is an AI-powered industrial analytics and operational intelligence platform built specifically for process manufacturing industries. It enables process engineers, operations managers, and data scientists to search, clean, contextualize, and model large volumes of complex time-series data. Operating on top of industrial historians and IoT databases, Seeq accelerates diagnostic, predictive, and descriptive analytics across plants. The platform features point-and-click tools, machine learning capabilities, and enterprise monitoring dashboards to boost production efficiency and reliability.

Founder story

Seeq was founded in 2013 in Seattle, Washington, by Steve Sliwa, Brian Parsonnet, Jon Peterson, and Mark Derbecker. Drawing from prior leadership at companies like OSIsoft, Honeywell, and Insitu, the founders recognized that process manufacturing plants generated massive time-series data but lacked intuitive tools to analyze it efficiently. They created Seeq to bridge the gap between raw operational technology data and actionable business intelligence.

What it does

• Connects directly to operational technology (OT) historians, SQL databases, and cloud data lakes without data duplication
• Provides interactive visual analytics tools for engineers to clean, aggregate, and contextualize high-frequency time-series signals
• Deploys AI and machine learning algorithms for automated pattern detection, anomaly tracking, and asset failure prediction
• Facilitates real-time enterprise monitoring and collaborative reporting across global manufacturing facilities.

Who it's for

• Process & Chemical Engineers
• Operations & Reliability Managers
• Industrial Data Scientists
• Enterprise Sustainability Officers

Why it works

• Purpose-built for time-series data structures that conventional general-business intelligence tools handle inefficiently
• No-code and low-code interfaces allow frontline process engineers to build predictive models without writing code
• Live data connectors integrate directly with legacy OT platforms like AVEVA PI System, Honeywell, and OSIsoft
• Enterprise scalability enables cross-plant bench-marking, knowledge sharing, and enterprise-wide asset tracking.

Growth strategies

• Co- selling and technical partnerships with major cloud providers including AWS, Microsoft Azure, and Google Cloud
• Direct enterprise sales targeting Fortune 500 chemical, pharmaceutical, oil & gas, and power generation enterprises
• Strategic corporate investments and distribution through industrial technology partners like Saudi Aramco Energy Ventures and Cisco Investments
• Community engagement through user groups, certified training programs, and industrial digital transformation thought leadership

Alternatives

• Tractian
• Shoplogix
• TrendMiner
• Uptake

Comparison overview

• Seeq focuses specifically on interactive time-series data analysis and OT historian integration for process manufacturing.
• Unlike general BI platforms like Power BI, Seeq provides built-in signal processing, cleansing, and contextualization tools natively.
• Offers direct live query execution against OT data lakes without requiring batch ETL exports into relational databases.