Seeq
About Seeq
Seeq is a time data analytics and collaboration platform designed for process manufacturing and industrial operations, enabling engineers and operators to rapidly analyze time series data, detect anomalies, and optimize performance across production, quality, and maintenance workflows.
Trend Decomposition
Trigger: Increased availability of industrial time series data and need for faster root cause analysis in process industries.
Behavior change: Teams adopt self serve analytics, share notebooks, and run ad hoc analyses to drive improvements without heavy IT intervention.
Enabler: Cloud based data platforms, open data formats, and integrated visualization/collaboration features that lower barriers to entry.
Constraint removed: Reduced reliance on specialized data science teams; faster access to actionable insights at the point of operation.
PESTLE Analysis
Political: Regulatory compliance and traceability requirements in regulated process industries drive demand for auditable analytics.
Economic: Costly downtime and yield losses incentivize investment in predictive analytics and process optimization.
Social: Collaboration between engineering, operations, and digital teams becomes more common, accelerating data driven decisions.
Technological: Growth of time series databases, OT IT convergence, and AI assisted analytics enable deeper insights from industrial data.
Legal: Data governance and cybersecurity considerations shape how industrial data is collected, stored, and shared.
Environmental: Improved process efficiency reduces energy consumption and emissions, aligning with sustainability goals.
Jobs to be done framework
What problem does this trend help solve?
It helps engineers quickly identify root causes of process upsets and optimize performance using time series data.What workaround existed before?
Manual data collection, dashboards, and siloed Excel analyses with slow cross functional coordination.What outcome matters most?
Speed and certainty of insights, with cost effective improvements and minimized downtime.Consumer Trend canvas
Basic Need: Access to trustworthy, actionable time series insights for industrial decision making.
Drivers of Change: Digital transformation in manufacturing, OT IT integration, and demand for proactive maintenance.
Emerging Consumer Needs: Shared analytics workflows, collaboration across teams, and auditable analytics trails.
New Consumer Expectations: Real time, explainable insights with reproducible analyses and strong data governance.
Inspirations / Signals: Case studies showing reduced downtime and increased yield from data driven interventions.
Innovations Emerging: AI enhanced anomaly detection, predictive maintenance, and integrated OT IT analytics platforms.
Companies to watch
- Seeq - Core provider of time series analytics for process industries.
- AspenTech - Industrial AI and optimization software for process industries; analytics enabled planning and asset optimization.
- Schneider Electric - OT IT convergence, industrial automation, and data analytics for energy and process optimization.
- Honeywell - Industrial digital transformation and analytics solutions for process industries.
- AVEVA - Industrial software for engineering and operations with data analytics capabilities.
- Osisoft (PI System) - Time series data infrastructure for industrial analytics and operations.
- Rockwell Automation - Industrial automation and analytics solutions integrating OT data with IT workflows.
- Siemens Digital Industries - Industrial software and analytics for manufacturing and process industries.
- Emerson Electric - Industrial automation and analytics for process optimization and reliability.
- GE Digital - Industrial IoT, data analytics, and asset performance management solutions.