Industrial AI Analytics
Arundo Analytics
SF 7.9Industrial AI for asset analytics
Contact sales
Industrial AI Analytics
Seeq Analytics
SF 8.7Self service analytics for process data
Contact sales
Quick decision guide
Choose based on your workflow
Arundo Analytics may fit better if...
- Model Deployment
- Edge Runtime
- Data Connectors
Seeq Analytics may fit better if...
- Time Series Search
- Calculation Engine
- Operational Dashboards
Overview
How each tool is described
Arundo Analytics
What is Arundo Analytics?
Arundo Analytics provides industrial AI software for asset-heavy and process-intensive sectors, combining operational data, time-series information, knowledge graphs, machine learning, and AI agents to support equipment monitoring, optimization, and operational decision-making. Its current portfolio combines the Arundo AI Foundation, AI Companion, cloud applications, and tailored industrial AI solutions.
- Industrial analytics: Arundo AI Foundation connects existing industrial data sources, represents assets, sensors, models, and documents through a knowledge graph, stores time-series data, and orchestrates analytical and machine-learning models. Foundation Studio also lets teams inspect data provenance and lineage and configure the industrial domain.
- AI assistance: AI Companion lets operations teams ask natural-language questions across sensor telemetry, maintenance records, equipment manuals, knowledge-graph relationships, and model outputs. Responses can include graphical and tabular results, while source review and trace-back show which underlying data contributed to an answer.
- Operational fit: ArundoEdge streams IoT sensor data from industrial control systems to the cloud, while EdgeManager handles deployment and monitoring of machine-learning models. Current specialized applications include Marathon for equipment monitoring and prescriptive maintenance, CarbonPath for maritime Scope 3 emissions management, and Energy Optimizer for optimizing industrial electricity consumption and cost.
- Commercial considerations: Arundo offers both cloud-delivered SaaS applications and tailored AI solutions built on its Foundation technology. Public list pricing is not provided, so buyers should evaluate the required applications, data integrations, deployment architecture, industrial modeling scope, and implementation services when assessing total cost and project complexity.
Arundo is particularly relevant to industrial organizations that need AI grounded in interconnected assets, sensor histories, engineering documents, and operational models rather than general-purpose business analytics or standalone generative AI.
Seeq Analytics
What is Seeq Analytics?
Seeq is an industrial analytics, AI, and enterprise monitoring platform built for engineers, operations teams, and data scientists working with time-series process data. Its browser-based applications include Workbench for analysis, Organizer for reporting, Data Lab for Python workflows, and Vantage for monitoring large numbers of assets and operational events.
- Industrial analytics: Seeq Workbench provides no-code and low-code tools for cleansing data, defining operating periods, performing calculations, modeling behavior, making predictions, and investigating equipment or process performance. Its Formula language adds more advanced transformations and calculations when point-and-click tools are not sufficient.
- Reporting and enterprise monitoring: Organizer turns Workbench analyses into interactive dashboards and reports that can update with current data manually or on a schedule. Vantage provides a separate enterprise-monitoring workflow that aggregates conditions and events across large numbers of sensors and assets, helping teams triage and investigate predictive-maintenance issues, downtime, alarms, and other operational exceptions. Vantage requires additional licensing.
- Industrial data connectivity: Seeq connects directly to historians, SQL databases, data lakes, and other industrial data systems through supported connectors and Remote Agents. Connected source systems remain authoritative: Seeq retrieves and caches their data for calculation and visualization rather than replacing the historian or creating a new system of record. Buyers should therefore evaluate connector availability, network access, source-system performance, latency, and data quality.
- AI and Python workflows: Seeq AI Assistant includes agents for tasks such as writing formulas, performing analyses, creating Seeq content, assisting with reports, and automating repeatable multi-step workflows. Data Lab provides a JupyterLab environment with Python, the Seeq/Python library, machine-learning libraries, scheduled jobs, and custom analytics. AI availability is deployment- and license-dependent: the current AI Assistant is offered to eligible SaaS customers, while capabilities such as Agent Q and custom Agent Builder workflows require Seeq Intelligence licensing.
Seeq is most relevant to industrial organizations that already hold substantial process and asset data in historians or other operational systems and want engineers to analyze that data without repeatedly exporting it into spreadsheets or separate analytics silos. Its value depends on data connectivity, engineering adoption, monitoring scale, licensing requirements, and whether faster analysis and exception-based monitoring can materially improve operational decisions across assets and plants.
Side-by-side
Key differences
Criteria
Industrial AI AnalyticsArundo Analytics
Industrial AI AnalyticsSeeq Analytics
Best for
Industrial AI Analytics
Industrial AI Analytics
Score
7.9/10
8.7/10
Pricing
Contact sales
Contact sales
Category / audience
AI Maintenance, CMMS & Asset Reliability Software › Industrial AI Analytics
- industrial ai
- oil and gas
- machine learning operations
AI Maintenance, CMMS & Asset Reliability Software › Industrial AI Analytics
- seeq
- process analytics
- time series analytics
Feature check
Side-by-side feature check
Feature
Arundo Analytics
Seeq Analytics
Model DeploymentTools for moving ML models into production
-
Edge RuntimeRuns models close to industrial assets
-
Data ConnectorsReads from historians sensors and ERP systems
-
Performance AppsReusable applications for reliability and performance
-
Model MonitoringWatches drift and accuracy in production models
-
Industrial TemplatesPatterns for oil gas shipping and power
-
12 capabilities compared.12 differentiating rows are shown first.
Use cases
Who they're built for
Arundo Analytics
- Deploy machine learning models into productionMove models from notebooks into reliable production environments
- Run edge analytics close to assetsProcess sensor data near assets for low latency
- Operate offshore asset analytics across fleetsApply analytics to oil rigs and shipping fleets
Seeq Analytics
- Investigate process plant events and anomaliesSearch historian data to understand specific abnormal events
- Build asset performance dashboards for engineersCreate live views of critical process equipment behavior
- Support reliability engineering analysis and decisionsHelp reliability teams analyze recurring failures and patterns
The trade-offs
Pros & cons of each tool
Trade-offs
Arundo Analytics
Pros
- Helps move models into reliable production environments
- Edge runtime suits distributed industrial asset deployments
- Strong focus on real industrial use cases
Cons
- Targeted at organizations with internal data teams
- Less suitable as a standalone packaged product
- Smaller market footprint than large industrial platforms
Trade-offs
Seeq Analytics
Pros
- Powerful time series analytics for process engineers
- Connects to many industrial historians and sources
- Encourages collaboration across reliability and process teams
Cons
- Needs strong historian data and engineering capacity
- Less suited for plants without process data history
- Pricing scales with users and connected sources
Final verdict
Best fit depends on your workflow
Current catalog data shows meaningful overlap between Arundo Analytics and Seeq Analytics. Use the signals below to decide based on workflow, ecosystem, pricing, and implementation fit.
Differentiators available
Arundo Analytics has 4 visible decision signals and Seeq Analytics has 4.
Score signal
Seeq Analytics has the higher SoftFinders Score in the current catalog data.
Choose Arundo Analytics if…
- Deploy machine learning models into production
- Run edge analytics close to assets
- Operate offshore asset analytics across fleets
- Model Deployment
Choose Seeq Analytics if…
- Investigate process plant events and anomalies
- Build asset performance dashboards for engineers
- Support reliability engineering analysis and decisions
- Time Series Search
TRY THEM YOURSELF
See which one fits your workflow
Both tools have their strengths, the best way to decide is to spend a few minutes inside each.