SepaIQ Data Management & Analytics

Transform production data across sites and systems into trusted manufacturing intelligence.

Where Manufacturing Data Comes Together

SepaIQ is a manufacturing data management and analytics platform that brings together production data from equipment, sites, and systems into a consistent, contextualized structure. Teams can define reusable models, calculations, and logic, then share reliable manufacturing intelligence with BI, AI, and enterprise applications.

THE CHALLENGE

Barriers to Trusted Analytics

Reliable analytics start with reliable manufacturing data. When production data is fragmented, missing operational context, or calculated differently from one place to another, teams cannot trust the results.

Scattered Data

Data lives in separate systems. Every project requires custom clean-up work before any real progress can begin.

With SepaIQ

Missing Context

Raw data is not connected to the context that gives it meaning. Teams can see what happened, but not why.

With SepaIQ

Data You Can’t Trust

Metrics and KPIs do not match across systems, and teams cannot rely on the numbers.

With SepaIQ

What You Can Do with SepaIQ

Move beyond one-off data work and build repeatable ways to use manufacturing information throughout your operation.

Make Data Meaningful

Connect production data to equipment, products, materials, orders, and other operational context.

Standardize Across Operations

Apply common models, calculations, and logic consistently to equipment, lines, sites, and systems.

Build & Reuse Analytics

Create custom calculations, KPIs, analytics, and logic that go beyond out-of-the-box metrics.

Keep Results Current

Keep reporting and analytics aligned with live production changes, post-production updates, and corrections.

Put Insights to Work

Share contextualized data and analysis results with plant-floor, BI, AI, and other enterprise applications.

Scale Analytics Efficiently

Centralize resource-heavy calculations and analytics so plant-floor systems stay focused on production execution.

HOW IT WORKS

Connect, Contextualize, Analyze

Turn diverse manufacturing data into intelligence your entire organization can use. SepaIQ brings together data from across production, adds operational context, applies reusable logic and analytics, and delivers trusted results to plant-floor and enterprise systems.

CORE CAPABILITIES

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.

Configurable Data Structure

Structure and contextualize manufacturing data around your operation. Build hierarchies using ISA-95, a modified standard, or a custom framework that reflects how your organization is actually structured.

Real-Time Plant Floor Updates

Connect SepaIQ with Ignition® by Inductive Automation to deliver analytics results back to the people who can act on them in real time and respond more quickly to emerging issues.

SepaIQ Platform & Modules

Start with the SepaIQ Platform, then add enterprise, connectivity, and AI capabilities as your requirements evolve.

SepaIQ Module Features

A quick reference for module selection and architecture planning.

SepaIQ Platform

Required with every SepaIQ module purchase.

The SepaIQ foundation built for high-performance manufacturing analytics, including custom calculations, unlimited flexible data groups, reusable templates, and more.

FEATURE
dESCRIPTION

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.

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.

BUILT-IN CALCULATORS

Use pre-defined SPC and OEE calculations to evaluate performance, losses, and variability using consistent, industry-standard metrics.

SEPASOFT MES INTEGRATION

Use the high-quality Batch, OEE, and SPC data from your Sepasoft MES system as the foundation for centralized analytics in SepaIQ.

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.

Supported databases: MySQL, SQL Server, MariaDB, PostgreSQL, Redshift

EXTERNAL DATABASE PUBLISHING

Send analysis results or contextualized data from SepaIQ to external SQL databases so downstream systems and BI tools can use clean, structured information.

ACCESS MANAGEMENT

Control how users access and interact with SepaIQ using user-level permissions and OpenID-based authentication, ensuring secure sign-in and appropriate read, request, and edit access based on user responsibilities.

REST API INTERFACE

Enable full bidirectional interaction with SepalQ. Beyond simple data ingestion, external systems can subscribe to analytics requests, modify historical records, and query the LLM directly.

USER TEMPLATES

Save common data group designs or analysis setups as templates so teams can reuse proven configurations throughout lines, products, and sites.

NATIVE IGNITION INTEGRATION

Connect Ignition and SepaIQ directly to offload centralized analytics from plant-floor systems while returning calculated results to Ignition in real time.

Enterprise Module

Scale securely to multiple 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 between 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.

PROCESS DATA CHANGE LOG

Record every change made to process data so teams can review what changed, who changed it, and when. This keeps historical analysis accurate and trustworthy.

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.

MQTT V5 CONNECTOR

Use MQTT v5 features such as shared subscriptions and user properties when subscribing to event streams that need richer metadata.

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.

AZURE IOT HUB CONNECTOR

Push SepaIQ data into Azure IoT Hub so cloud services, analytics pipelines, and downstream applications can consume structured production data from a centralized IoT messaging platform.

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.

SENTIMENT ANALYSIS

Analyze operator comments, log entries, or other textual fields to uncover trends, concerns, or early warnings that support predictive quality and maintenance.

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

Support decision-making across multi-national facilities by enabling users to interact with the same underlying data model using their local language.

Scroll to Top