Power analytics with trusted production data.
SepaIQ is a manufacturing analytics platform that organizes MES and production data so teams can analyze performance, predict losses, and scale analytics with confidence.
MES Data PLATFORM FOR MANUFACTURING ANALYTICS
Barriers to Trusted Analytics
AI is on everyone’s roadmap, but many manufacturers still struggle to get consistent numbers from the data they already have. SepaIQ helps you clear the barriers first, so analytics become reliable and AI has trustworthy inputs to learn from.
Scattered Data
Data lives in separate systems. Every project requires custom clean-up work before any real progress can begin.
- Link events, equipment, materials, and people in a unified model
- Deliver clean, structured data ready for analytics and AI
Missing Context
Raw data is not connected to the MES context that gives it meaning. Teams can see what happened, but not why.
- Connects time-series data to batches, materials, and equipment
- Add meaning to raw data so teams can act with confidence
Data You Can’t Trust
Metrics and KPIs do not match across systems, and teams cannot rely on the numbers.
- Standardize logic to produce consistent KPIs and metrics
- Provide consistent data for decisions across systems
what You can do with SepaIQ
Each manufacturer starts with a different goal. SepaIQ supports a wide range of use cases, from improved OEE analysis to machine learning–driven quality, reliability, and optimization.
Predict loss before It happens
- Surface hidden drivers behind downtime and production losses
- Predict which lines, products, or conditions are most at risk next
- Prioritize action before losses show up in KPIs
Predict Quality Drift and Reduce Scrap
- Detect early indicators of quality drift across materials and processes
- Predict scrap risk before defects appear
- Intervene sooner to protect yield and throughput
Standardize Enterprise Analytics
- Apply consistent analytics models across lines and sites
- Eliminate manual enterprise aggregation and rework
- Compare performance confidently at scale
How SepaIQ fits into your manufacturing stack
SepaIQ acts as the layer between production systems and downstream analytics and AI. It organizes and contextualizes production data so metrics stay consistent and dependable.
Production Sources
Ingest data from wherever it lives, including control, execution, and business systems.
Structure and contextualize production data in one managed layer, so every downstream system runs on the same logic.
- Unified real-time and historical analytics
- Synchronize analytics after data corrections
- Native machine learning and LLM capabilities
Trusted Analytics and AI
Deliver model-ready data to the tools teams already use, for consistent results across systems and sites.
SepaIQ modules for analytics, connectivity, and AI
SepaIQ modules are designed to scale with your use cases. Start with Advanced Analytics, then layer in Enterprise, Connectors, LLM, and Machine Learning modules as requirements evolve.
Advanced Analytics Module
Central analytics layer where data is shaped, calculations run, and all customized analysis is made possible.
- Build custom KPIs and calculations
- Standardize analytics across sites
Enterprise Module
Designed for growing teams that need structured access, reliable change tracking, and controlled deployments.
- Project-based access controls
- Deploy updates with review, rollback, and accountability
Incoming Connector Module
Ingest event-driven data from external systems using Kafka, MQTT, and other protocols.
- Stream data from a wide variety of production data sources
- Combine production, quality, and enterprise events in one place
Outgoing Connector Module
Deliver SepaIQ results and event data to external systems using Kafka and Azure event services.
- Send formated analysis results directly to AI and BI platforms
- Share structured, event-ready data with downstream consumers
Machine Learning Module
Build, train, and run machine learning models using clean, contextualized production data.
- Predict production loss and quality issues before they occur
- Analyze operator notes to detect trends or concerns early
LLM Module
Make production data easier to use with a chat-style interface for questions and summaries.
- Ask natural-language questions about production, downtime, or quality
- Create clear summaries of batches, shifts, and recent events
Built on Trusted Data, Ready for AI
When your data is consistent and contextualized, you can move beyond reporting. SepaIQ helps teams predict production loss and quality issues, surface trends in operator notes, and explore results through a natural-language chat experience.
Built for the Reality of Manufacturing Data
Handle the scale, complexity, and constant changes of plant-floor information with confidence.
High-Performance Analytics
Critical systems like HMI, SCADA, and MES can push production servers to their limits. SepaIQ offloads analytics to a server cluster, distributing workloads without overburdening production systems.
Post-Production Updates
Manufacturing data is never static. Downtime reasons get corrected, lab results arrive later, and records evolve. SepaIQ saves changes only when values change and keeps related data in sync.
Data Contextualization
SepaIQ links raw events to production context, like equipment, materials, batches, and people. That turns “what happened” into “why it happened,” so analytics and AI results are more reliable.
Real-Time Plant Floor Updates
SepalQ analyzes data, performs predictions, and delivers valuable insights back to the people who can act on them in real time. Teams can respond faster to quality risks, downtime drivers, and emerging issues.
See It In Action
Watch the platform in action, explore our modular licensing, or dive deeper into data architecture strategies.
Watch the Demo
Watch our SepaIQ webinar to see real-time analytics and AI-driven insights in action.
Pricing & Licensing
Explore our flexible pricing. Mix and match the specific modules and server scale that fit your project.
MES Context & UNS
Learn how incorporating MES context unlocks the true value of your Unified Namespace.
SepaIQ Platform
Required with every SepaIQ module purchase.
The foundation of the SepaIQ ecosystem. Collect production data and structure it with simple grouping and calculations to prepare it for advanced analytics and AI.
FEATURE
dESCRIPTION
BUILT-IN AGGREGATION CALCULATORS
Use simple built-in functions such as sum, average, minimum, maximum, and count to create basic summaries of your production data.
Includes up to 20 custom data groups, with up to 20 items per group.
LIMITED CUSTOM DATA GROUPS
Define a limited set of data groups to organize production information according to your equipment, products, and processes.
REST API INTERFACE
Enable full bi-directional interaction with SepalQ. Beyond simple data ingestion, external systems can subscribe to analytics requests, modify historical records, and query the LLM directly.
Native Ignition integration coming soon in 2026.
IGNITION INTEGRATION
Bring real-time production data from Ignition into SepaIQ through scripting or REST API so analytics and machine learning models can use the information already collected in your Ignition projects.
Native Sepasoft integration coming soon in 2026.
SEPASOFT MES INTEGRATION
Use the high-quality Batch, OEE, and SPC data from your Sepasoft MES system as the foundation for analytics in SepaIQ, connecting through scripting or REST API.
Advanced Analytics Module
Unlock high-performance analytics with custom calculations, unlimited flexible data groups, reusable templates, and external database connections.
FEATURE
dESCRIPTION
CUSTOM CALCULATIONS
Build custom metrics with drag-and-drop tools and basic JavaScript to calculate cycle efficiency, quality ratios, material usage, or any plant-specific KPIs tailored to your operations.
SPC AND OEE BUILT-IN CALCULATORS
Use pre-defined SPC and OEE calculations to evaluate performance, losses, and variability using consistent, industry-standard metrics.
Limited by server performance and available system resources
UNLIMITED CUSTOM DATA GROUPS
Define unlimited logical groups of production data aligned to your equipment, products, and processes. Organize data using ISA-95 structures, UNS conventions, or custom hierarchies that fit your operations.
USER TEMPLATES
Save common data group designs or analysis setups as templates so teams can reuse proven configurations across lines, products, and sites.
Supported databases: MySQL, SQL Server, MariaDB, PostgreSQL, Redshift
READ-ONLY DATA GROUPS
Include external data from ERP, quality, historian systems, and databases as read-only inputs so production, quality, and business data can be analyzed together.
Enterprise Module
Scale securely across sites and teams with project-based access, CI/CD-ready deployment management, and robust change tracking.
FEATURE
dESCRIPTION
PROJECT-BASED ACCESS CONTROL
Assign users to specific workspaces so they only see the data groups associated with that project. Analytics and LLM responses stay limited to the data each person is authorized to access.
PROJECT-BASED RESOURCES
Assign data groups, models, connectors, and templates to specific workspaces so each project has its own clear set of resources. This keeps analysis, data flows, and configurations organized and separated across projects or sites.
CI/CD SUPPORT
Manage configuration changes across development, test, and production environments using repositories (e.g., Git) for secure, versioned deployment workflows.
Incoming Connector Module
Stream MES, quality, maintenance, and external production data into SepaIQ using Kafka, MQTT, and other event-driven protocols.
FEATURE
dESCRIPTION
SPARKPLUG CONNECTOR
Subscribe to Sparkplug MQTT topics so SepaIQ can consume structured, stateful messages from SCADA and edge devices.
KAFKA CONNECTOR
Ingest high-throughput event streams from Kafka topics so large volumes of time-series data arrive in SepaIQ with minimal latency.
MQTT V3 CONNECTOR
Consume MQTT v3 topics from brokers such as a Unified Namespace so sensor and MES events stream directly into SepaIQ.
Outgoing Connector Module
Send contextualized production data and analytics results to external systems through supported event-driven connectors, enabling real-time integration with BI, AI, and cloud platforms.
FEATURE
dESCRIPTION
KAFKA CONNECTOR
Publish high-throughput event streams from SepaIQ to Kafka topics so data lakes, pipelines, and enterprise systems can consume analytics-ready information with minimal latency.
AZURE EVENT GRID CONNECTOR
Push SepaIQ updates into Azure Event Grid so cloud services, serverless functions, and business applications can react to production events in real time.
Machine Learning Module
Build and run predictive models that look for patterns in production data to flag early signs of downtime, losses, quality risks, and process deviations before they affect performance.
FEATURE
dESCRIPTION
BUILT-IN PREDICTION MODELS
Use built-in ML models to predict losses, failures, and quality issues without needing to design algorithms from scratch.
MODEL TUNING & TRAINING
Evaluate how a model performs on real production data using clear training results and scoring metrics. Fine-tune and retrain the model to improve accuracy and confidence before relying on predictions in operational decisions.
SEAMLESS INTEGRATION WITH ANALYSIS
Run prediction models directly within analysis to keep results tied to the same data, filters, and calculations teams already trust. This makes predictions easier to validate, compare, and use without switching tools or reworking data.
LLM Module
Integrate with large language models, enabling teams to ask plain-language questions and quickly get accurate, data-backed explanations of production events, issues, and trends.
FEATURE
dESCRIPTION
GENERATIVE AI & LLM INTEGRATION
Leverage SepaIQ’s native LLM-ready data model to enable conversational analytics without building custom pipelines, prompts, or data-preparation workflows.
CONVERSATIONAL ANALYTICS
Let teams explore production data using natural language instead of queries, scripts, or dashboards.
SECURE LLM ACCESS
SepaIQ acts as the intermediary between your production data and the LLM. Sensitive data stays inside your environment, and only authorized information is sent to or used by the model.
LLM REQUEST REVIEW & VALIDATION
Insert a scripting layer between the LLM and SepaIQ analysis to review and adjust requests before they run. This allows teams to enforce rules, standardize formats, and keep LLM-driven analysis aligned with approved analytics behavior.
LLM ACCESS CONTROL
Define which analysis parameters the LLM can reference or modify when running analysis. This helps limit access to sensitive properties, prevent misleading queries, and keep AI-generated results consistent with approved reporting and analysis practices.
MULTI-LINGUAL SUPPORT
Ensure consistent decision-making across multi-national facilities by enabling users to interact with the same underlying data model using their local language.