Cognite Data Fusion - Product Release Dashboard

Cognite Data Fusion Product Updates

Discover how these updates empower your data-driven operations

Features released

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Release

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Data Sources

OPC

SAP

OSIsoft

opentext

MQTT

+90 more

Data Onboarding

Source System Extractors

Data Workflows

Engineering Diagram Parsing

Entity Matching

3D Contextualisation

Functions

Transformations

Industrial Knowledge Graph

Data Modeling

Time Series

3D

Files

Point Clouds

Geospatial

Annotations

Units of Measure

Data Management

Data Exploration & Profiling

Data Catalogue

Access Management

Atlas AI™

Agent Builder

LLM Benchmarking

Agent Library

Industrial Applications

Search

Field Operations

Robotics

Industrial Canvas

Charting & Analytics

Maintenance Planning

Consume and Integrate

Grafana

Power BI

GraphQL

REST API

Python

JavaScript

Simulator Connectors

Multi-cloud, Security & Quality

Google Cloud

AWS

Azure

OpenID

ISO 27001

Release Details

No matching release notes found.

MAR 3, 2026

Simulators UI

Beta Simulator Integration Accelerated time to value

Subject Matter Experts are no longer blocked by a "technical wall." A new no-code interface empowers SMEs to independently configure simulator models and orchestrate logic visually with a drag-and-drop Routine Board.

Problem:

SMEs were blocked by a "technical wall" — simulator connectors remained locked behind APIs that could only be configured by developers.

Now:

Empower SMEs to independently configure their own models and use a no-code "Routine Board" for drag-and-drop visual logic orchestration — no developer dependency required.

Documentation →

MAR 3, 2026

Chart - activities overlay

Charts New Release Reduce the amount and cost of downtime Increase industrial workforce capacity

Overlay activity types — such as work orders — directly onto time series in Charts to correlate operational context with time series behavior.

Problem:

Industrial users struggled to correlate data trends with real-world operational events, having to cross-reference separate systems manually.

Now:

Overlay activity types — such as work orders — directly onto time series in Charts to instantly connect anomalies with the "why."

Added Value:

Activities brings operational context (work orders, maintenance, inspections) directly into Charts so users can correlate events with time series behavior in the same workflow. This reduces investigation time and helps teams identify root causes faster, supporting quicker recovery and less unplanned downtime.

Documentation →

MAR 3, 2026

3D MiniMap navigation

3D New Release Accelerated time to value

Use customizable real-time minimaps to track your camera position and "fast-travel" through 3D scenes by clicking destinations on the map. Never lose orientation again.

Problem:

When navigating 3D scenes in Search, it was easy to lose orientation and real-world context, especially in large or complex facilities.

Now:

Customizable real-time minimaps track your camera position and allow "fast-travel" through the scene by clicking destinations on the map.

Added Value:

Increased productivity for users by making navigation to assets in 3D quick, seamless and intuitive. The Minimap eliminates navigation fatigue - ensuring they spend less time "flying" and more time executing tasks.

Documentation →

MAR 3, 2026

New 3D experience in Search

Search 3D Accelerated time to value Increase industrial workforce capacity

Finding an asset is one thing; understanding its surroundings is another. The upgraded 3D Experience in Search gives you instant spatial context without ever leaving your search results.

What's New:

In-Preview Scenes & 360° Images — View 3D scenes and 360-degree images directly in the search preview pane.
Seamless Transitions — Move from a search preview to the unified 3D world while staying immersed in your 360° view.
Direct Access — Launch full Scenes immediately from the preview card.

Problem:

Users lacked 3D scenes in search previews, leaving them without spatial context for model placement. Navigating to a separate 3D viewer broke the workflow.

Now:

View 3D Scenes and 360° images directly in the search preview to gain immediate context for a selected Location. Opening the full 3D view from a 360° preview even maintains your exact orientation — no more "re-finding" the asset once the viewer loads.

Quick Start:

Prepare — Ensure you are using Scenes for 3D and that they are connected to your Location.
Search for an asset or location in CDF.
Preview the result to see the 3D scene load automatically.
Explore by opening the unified 3D view for full immersion.

Added Value:

Faster time to value for users by providing full real-world context within search results, removing the need to switch between 3D and Search.

Documentation →

MAR 3, 2026

Smarter search results

Opt-in Beta Search Time to value

Advanced "Industrial Parsing" for higher number of searchable terms, and a matching logic prioritizing result accuracy over quantity. Handles partial industrial tags and complex strings that standard search fails on. GA planned for April 2026.

Problem:

Standard search often failed to handle partial industrial tags or returned broad, inaccurate results for complex strings.

Now:

Additional parsing and tokenization for significantly higher precision searches for tag-like naming structures usually consisting of letters and numbers, optionally delimited by various symbols. Applicable for search on Core Data Model.

Added Value:

Strengthen user trust in search results. More accurate, precise searches leads to reduced time to find relevant data. Increased ease-of-use by search supporting partial matches - an expectation by users.

Documentation →

MAR 3, 2026

File upload via Search UI

Search New Release Increase industrial workforce capacity Time to value

Upload single files — such as RCA templates — directly through the Search UI without relying on technical pipelines. Search also works as a resource selector in tools like Industrial Canvas.

Problem:

SMEs lacked a simple way to upload individual files, such as RCA templates, without relying on technical pipelines.

Now:

Upload single files directly through the Search UI and use Search as a resource selector in tools like Industrial Canvas. Upload is available for data modeling views.

Added Value:

Enabling end user without relying on central data engineers to complete their jobs to be done. Faster time to value by unblocking jobs to be done. Enriching the knowledge graph with data from unstructured sources.

Documentation →

MAR 3, 2026

Unit-aware Records

Beta Records Rapidly scaling use cases across your enterprise

Perform unit-aware querying, filtering, and aggregation within Records — eliminating the need for custom unit-conversion code when sensor values use different unit systems.

Problem:

Users had to manually convert sensor values when querying, filtering, or displaying data across different unit systems.

Now:

Perform unit-aware querying, filtering, and aggregation within Records to eliminate the need for custom unit-conversion code.

Documentation →

MAR 10, 2026

Atlas conversation history

Atlas AI New Release Reduce the amount and cost of downtime

Atlas agents now retain session history. Continue past chats where you left off or work across multiple parallel conversations without losing context.

Problem:

Atlas agents didn't retain session history, forcing users to restart workflows and lose context between sessions.

Now:

Continue past chats where you left off or work across multiple parallel conversations without losing context.

Added Value:

Workforce productivity gain, reduced downtime - keeping a trace of past and current work, like RCAs, and ability to have multiple ongoing work streams.

Documentation →

MAR 10, 2026

Per-agent granular access control

Atlas AI New Release Rapidly scaling use cases across your enterprise

Configure specific read, write, and run rights on a per-agent basis to ensure users only interact with authorized agents. Previously, all agents were visible to every user.

Problem:

All agents were visible to every user, and only creators could modify them — no fine-grained permissions existed.

Now:

Configure specific read, write, and run rights on a per-agent basis to ensure users only interact with authorized agents.

Added Value:

Scale - enable confidently putting agents in production, across sites and use cases.

Documentation →

MAR 3, 2026

Canvas performance boost

Industrial Canvas New Release Increased throughput Reduced downtime Workforce productivity gain Weeks to value

Industrial Canvas now loads 50% to 70% faster on average with up to 70% less memory usage during loading, delivering a significantly smoother experience for complex canvases.

Problem:

Increased load on Industrial Canvas caused sub-optimal load times and high memory consumption.

Now:

50% to 70% average reduction in load times and up to 70% less memory usage during loading.

Added Value:

70% to 97% RCA time reduction from the traditional way of working
Generating more than 1k work packages per year in Canvas
Up to 75% improved efficiency of piping integrity management

Documentation →

MAR 3, 2026

3D browser caching

3D New Release

Client-side browser caching for CAD and point cloud data delivers 63% faster 360 image loading and 52% less data transfer — providing instant loading for returning users.

Problem:

Increasing 3D data volumes led to performance degradation and suboptimal load times for large scenes.

Now:

Client-side browser caching for CAD and point cloud data enables 63% faster 360 image loading and 52% less data transfer, providing instant loading for returning users.

Documentation →

MAR 3, 2026

Diagram parsing - tag detection for Data Modeling

Data Onboarding New Release Increase industrial workforce capacity Accelerated time to value

Tag detection is now production-ready for Data Modeling, unblocking users migrating from asset-centric models. Built-in per-file parsing status provides full visibility into progress.

Problem:

Tag detection wasn't ready for Data Modeling, blocking users from migrating from asset-centric models.

Now:

Production-ready tag detection for Data Modeling with built-in per-file parsing status for full migration visibility.

Added Value:

By bringing tag detection for Data Modeling to GA, customers can confidently use it in day-to-day work to contextualize engineering diagrams, so industrial users can rely on contextualized diagrams and gain productivity. Built-in per-file parsing status removes the need for custom status tracking, improving transparency and reducing operational overhead, so we get to value faster.

Documentation →

MAR 3, 2026

Transformations - full metrics in run history

Data Onboarding New Release Rapidly scaling use cases across your enterprise

Access the full library of API-tracked metrics — including searchable selectors — directly within the Transformations Run History UI, making debugging and rate limit tracking transparent.

Problem:

The UI previously showed limited metrics, making it difficult to fully debug issues or track specific rate limits.

Now:

Access the full library of API-tracked metrics, including searchable selectors, directly within the Transformations Run History UI.

Added Value:

Providing full visibility into rate limits and API performance metrics is essential for managing a large-scale data foundation. It allows operators to resolve performance bottlenecks instantly without scaling the manual effort required for deep-system debugging.

Documentation →

MAR 3, 2026

Email notifications

Beta Data Workflows Rapidly scaling use cases across your enterprise

Configure automated email alerts for workflow failures, timeouts, and trigger issues to ensure stakeholders are informed the moment a pipeline needs attention.

Problem:

Users previously had to manually monitor CDF to track workflow statuses, often leading to delayed responses when critical pipelines failed or timed out.

Now:

Define specific subscribers (users or group addresses) to receive proactive email notifications that automatically include failures from any process orchestrated in workflows, such as Functions, Transformations or Simulators.

Added Value:

This is a critical feature for enabling customers to scale the number of data pipelines powering a scaled data foundation without proportionately increasing the manual effort required to monitor and operate them.

Documentation →

MAR 3, 2026

Event-driven triggers for Records

Beta Data Workflows Accelerated time to value with your use cases

Shift from schedule-based to event-based execution by triggering workflows the moment records data changes in a specific stream.

Problem:

Scheduled workflows cannot react immediately to real-time data changes, introducing latency that prevents agents and apps from utilizing the freshest information.

Now:

Automatically trigger workflows based on changes in Records with advanced filtering and configurable batch sizes, eliminating manual or time-based delays in your data pipelines.

Added Value:

This enables real-time responsiveness for industrial agents and dashboards, allowing them to provide value based on the most current operational state.

Documentation →

MAR 3, 2026

Workflow execution concurrency control

Data Workflows New Release Rapidly scaling use cases across your enterprise

Manage system performance and predictable data processing by setting a maximum limit on concurrent runs for each individual workflow.

Problem:

Unrestricted concurrent runs could lead to unpredictable system behavior or resource contention during periods of high data volume or overlapping schedules.

Now:

Use the new "maximum concurrent runs" setting in Workflow details to ensure consistent execution and better control over how your data processing resources are utilized.

Added Value:

Predictable execution limits provide the stability needed to scale hundreds of concurrent data pipelines across multiple facilities without compromising system performance.

MAR 3, 2026

Workflow monitoring & UI upgrades

Data Workflows New Release Rapidly scaling use cases across your enterprise

Monitor performance at a glance with new Overview columns and deep-dive into failed trigger attempts using the updated Run Details panel and filtering.

Problem:

Limited visibility on the Overview page and a lack of granular detail in execution logs made it time-consuming for engineers to debug performance bottlenecks. Furthermore, trigger failures were not visible at all, leading to "silently" failing workflows.

Now:

Access "Last run" and "Run status" columns directly in the Overview for at-a-glance health checks. The Run history list now explicitly includes "Failed trigger attempts" to eliminate silent failures. The updated Run Details panel provides comprehensive metadata, including trigger status, error messages, trigger type, and the identity of the user or service account that initiated the run. A new "Filter" button allows users to quickly find specific information by time range, workflow version, and run status.

Added Value:

By providing transparent, at-a-glance observability and streamlined debugging tools, customers can scale the complexity and volume of their data foundation while keeping the operational effort required to maintain system health under control.

DEC 2025

Faster, cleaner troubleshooting in Industrial Canvas

Beta Industrial Canvas

Complex diagrams became unreadable due to overlapping connection lines, slowing down troubleshooting. Now, the canvas is cleaner — hover over any connection path to instantly highlight that specific flow, increasing efficiency when troubleshooting.

Problem:

Complex diagrams became unreadable due to overlapping connection lines, slowing down troubleshooting.

Now:

Instant Flow Tracing — hover over any connection path to instantly highlight that specific flow. The canvas is cleaner and users can troubleshoot far more efficiently.

Documentation →

DEC 2025

Get immediate context: location prompt

User Experience New Release

New users often missed the critical Location filter, leading to poor data context and frustration. If a location is not selected, a pop-up prompt now appears, directing users to the filter and ensuring a greater set of users set the right context immediately.

Problem:

New users often missed the critical Location filter, leading to poor data context and frustration.

Now:

Contextual Prompting — if a location is not selected, a pop-up prompt appears directing users to the filter. This ensures the right context is set immediately, improving the data quality of their work.

Documentation →

DEC 2025

Seamless planning for frontline teams

Beta Field Operations

Supervisors lacked full visibility into what was planned for the upcoming weeks and control over what was published to frontline teams. The new Schedules tab provides full transparency into scheduled checklists, so supervisors can decide what is published and when.

Problem:

Supervisors lacked full visibility into what was planned for the upcoming weeks and control over what was published to frontline teams.

Now:

Full Schedule Control — the new Schedules tab provides full transparency into scheduled checklists. Supervisors can decide what is published to frontline teams and when, ensuring priorities are met. Users can also create checklists directly from the schedule.

Documentation →

DEC 2025

Smarter, faster 3D measurements

3D New Release

Measuring basic dimensions like pipe diameters was laborious and time-consuming. Now, perform one-click diameter measurements for pipes, vessels, and tanks — increasing the viability of using 3D to replace field work.

Problem:

Measuring basic dimensions like pipe diameters was laborious, requiring multiple steps and manual calculations.

Now:

One-Click Precision — perform one-click diameter measurements for pipes, vessels, and tanks. This increases the viability of using 3D to replace field work entirely.

Documentation →

DEC 2025

Customized 3D experience

3D New Release

Hardcoded default 3D settings forced users to manually adjust them per session. Now, define default Model Visibility, Rendering Quality, and Point Cloud settings per scene — reducing friction for regular users and improving the first-time experience.

Problem:

Hardcoded default 3D settings forced users to manually adjust them every session, creating friction.

Now:

Customizable Settings Per Scene — define default Model Visibility, Rendering Quality, and Point Cloud settings. This reduces friction for regular users and improves the first-time experience.

Documentation →

DEC 2025

Full 3D support for hybrid projects

3D New Release

3D was not fully supported by the Cognite Data Model (CDM) or hybrid projects, blocking customer migrations. New 3D service API endpoints for CDM enable a seamless 3D user experience in hybrid projects, unblocking migration to CDM.

Problem:

3D was not fully supported by the Cognite Data Model (CDM) or hybrid projects, blocking customer migrations.

Now:

Seamless Hybrid 3D — new 3D service API endpoints for CDM enable a seamless 3D user experience in hybrid projects. This enables migration to CDM and allows contextualization using both asset-centric and data modeling assets.

Documentation →

DEC 2025

Massive log and event data storage: Records API

Platform New Release

Billions of high-volume log entries and events overburdened the Knowledge Graph node structure, limiting scalability. The new Records API stores billions of structured records with seamless integration to Data Modeling, unlocking the next level of CDF scalability.

Why is this valuable:

Industrial operations generate massive volumes of log and event data. The Records API is purpose-built for this scale, handling billions of records without compromising the Knowledge Graph's performance on relational queries.

Problem:

Billions of high-volume log entries and events overburdened the Knowledge Graph node structure, limiting scalability.

Now:

Records API — store billions of structured records with seamless integration to Data Modeling. This unlocks the next level of CDF scalability.

Documentation →

DEC 2025

Full-field production optimization

Beta Workflows

Current CDF capabilities couldn't handle optimizing entire offshore fields with thousands of wells simultaneously. Now, run complex simulations across entire facilities, handling thousands of parameters and unlocking true field-wide production optimization.

Why is this valuable:

Optimizing an entire offshore field — not just individual wells — can unlock millions in additional production value. Large-scale workflow support makes this possible for the first time within CDF.

Problem:

Current CDF capabilities couldn't handle optimizing entire offshore fields with thousands of wells simultaneously.

Now:

Large-Scale Workflow Support — run complex simulations across entire facilities, handling thousands of parameters. This unlocks true field-wide production optimization.

Documentation →

DEC 2025

High-quality field observations

Field Operations New Release

Operators struggled to attach the correct asset to field observations, reducing data quality. Now, access the asset hierarchy to browse and find the correct asset on both mobile and desktop, ensuring observations are captured with the correct context.

Problem:

Operators struggled to attach the correct asset to field observations, reducing data quality and leading to poor decision-making.

Now:

Correctly Contextualized Observations — access the asset hierarchy to browse and find the correct asset on both mobile and desktop. This ensures observations are captured with the correct asset, leading to better decision making.

Documentation →

DEC 2025

Reliable workflow development

Workflows New Release

Complex workflow definitions made subtle errors difficult to find, leading to frustrating trial-and-error configuration. Now, perform comprehensive on-demand validation and auto-validation on publish, with errors surfaced, explained, and made actionable directly in the UI.

Problem:

Complex definitions made subtle errors difficult to find, leading to a frustrating trial-and-error configuration experience.

Now:

Actionable Validation — perform comprehensive on-demand validation and auto-validation on publish. Errors are surfaced, explained, and made actionable directly in the UI.

Documentation →

DEC 2025

Total process visibility: workflow triggers

Workflows New Release

Managing live pipelines was risky without clear visibility into automated starting points. Triggers are now shown as canvas nodes for full workflow visibility, delivering a true end-to-end visualization and enabling safe management of live pipelines.

Problem:

Managing live pipelines was risky without clear visibility into automated starting points (triggers).

Now:

Workflow Triggers as Nodes — triggers are now shown as canvas nodes for full workflow visibility. This delivers a true end-to-end visualization and enables safe management of live pipelines.

Documentation →

DEC 2025

Transparent document parsing (LLM Vision)

Beta Atlas AI

Users couldn't easily verify LLM parsing results because extracted values weren't visually linked to the source document. Now, extracted values are displayed with bounding boxes in the UI, making verification intuitive and trustworthy.

Problem:

Users couldn't easily verify LLM parsing results because extracted values weren't visually linked to the source document.

Now:

Visual Verification — extracted values are displayed with bounding boxes in the UI, making verification easier. You can also store data in a user-specified space.

Documentation →

DEC 2025

Streamlined annotation review for diagrams

Beta Data Onboarding

Users lacked an efficient way to verify and reject annotations, especially in bulk, and faced limitations when dealing with multi-page files. A dedicated review workflow with split UI tabs now makes annotation management fast and systematic.

Problem:

Users lacked an efficient way to verify and reject annotations, especially in bulk, and faced limitations when dealing with multi-page files.

Now:

Dedicated Review Workflow — the UI tabs are split into four distinct sections, with the first tab dedicated solely to reviewing annotations. Verify or reject file and asset annotations individually or in bulk, and manage annotations across multi-page files.

Documentation →

DEC 2025

Identify and optimize transformation inefficiency

Data Onboarding New Release

Transformations often re-processed and re-wrote large amounts of identical data, wasting compute resources and masking optimization opportunities. The Run History UI now displays a "No-Op" metric, instantly identifying inefficiency and driving smarter, incremental data loads.

Problem:

Transformations often re-processed and re-wrote large amounts of identical data, wasting compute resources and masking optimization opportunities.

Now:

Monitor "No-Op" Performance — the Run History UI now displays a "No-Op" metric, showing how many write operations were skipped because the data was unchanged. This instantly identifies inefficiency and drives smarter, incremental data loads.

Documentation →

DEC 2025

Data-driven agent confidence

Atlas AI New Release

Lack of visibility into agent performance or failures made it hard to build trust or troubleshoot. Now, create test sets and run evaluations to view pass/fail results, enabling data-driven confidence in agent reliability and smoother UAT.

Why is this valuable:

Moving AI agents from pilot to production requires evidence-based trust. Agent Performance Monitoring provides the data to prove reliability, identify regressions, and satisfy stakeholder requirements for production readiness.

Problem:

Blind Deployment — lack of visibility into agent performance or failures made it hard to build trust or troubleshoot issues.

Now:

Agent Performance Monitoring — create test sets and run evaluations to view pass/fail results. This enables data-driven confidence in agent reliability and supports smoother UAT.

Documentation →

DEC 2025

Precise and predictable agent queries

Atlas AI New Release

Agent queries could result in slightly different data or format, creating uncertainty in production workflows. Now, configure a specific query and lock fields, operations, and output to guarantee critical data is retrieved correctly and consistently every time.

Why is this valuable:

Production workflows demand deterministic output. Locking query configuration eliminates the unpredictability inherent in LLM-generated queries, making agents trustworthy for mission-critical data retrieval.

Problem:

Unpredictable Output — agent queries could result in slightly different data or format, creating uncertainty in production workflows.

Now:

Guaranteed Precision — configure a specific query and lock fields, operations, and output. This guarantees critical data is retrieved correctly and consistently every time.

Documentation →

DEC 2025

Enhanced Japanese search

Platform New Release

The existing search didn't account for the unique structure of Japanese, leading to poor relevance. Enhanced search capability now uses Morphological Analysis to provide relevant results, balancing precision and recall for Japanese-language queries.

Problem:

The existing search didn't account for the unique structure of Japanese, leading to poor relevance for Japanese-speaking users.

Now:

Morphological Analysis — enhanced search capability uses Morphological Analysis to provide relevant results, balancing precision and recall for Japanese-language content.

Documentation →

SEP 2, 2025

Smoother agent interactions

Atlas AI New Release

Cross-agent chat enables users to carry conversations fluidly across agents, reducing friction and keeping work moving. A refreshed UI aligns visually with CDF for smoother, more consistent interactions.

Why is this valuable:

Users can maintain context across multiple AI agents without starting over, creating a more natural and efficient workflow. The unified interface reduces cognitive load and accelerates problem-solving.

Before:

Users had to interact with each agent separately, losing context when switching between different AI capabilities. The UI felt disconnected from the main CDF experience.

Now:

Seamless conversations flow across agents with persistent context. The refreshed interface integrates naturally with CDF, making AI feel like a native part of the platform.

Documentation →

SEP 2, 2025

Smarter Knowledge Graph queries

Atlas AI New Release

The new Agentic QKG v2 unlocks richer, engineer-like insights. By supporting multi-step queries, diagram annotations, and edge properties, agents can now handle nuanced industrial questions.

Why is this valuable:

The enhanced QKG v2 enables engineers to ask complex, multi-layered questions about industrial systems and receive comprehensive answers. This dramatically reduces time spent navigating through multiple data sources.

Before:

Simple queries could only traverse basic relationships. Complex questions about system dependencies or multi-hop connections often hit dead ends, forcing users to manually piece together information.

Now:

Multi-step reasoning, diagram annotations, and edge properties unlock deep insights. Engineers can explore complex industrial relationships naturally, with the AI understanding context and providing engineer-level analysis.

Documentation →

SEP 2, 2025

Secure & governed agent operations

Atlas AI New Release

New access controls (agents:read, agents:write, agents:run) define who can view, create, or execute agents. High-impact tools like Python execution and REST API calls require explicit confirmation.

Why is this valuable:

Enterprise security and compliance are maintained while allowing innovation with AI. Organizations can confidently deploy AI agents knowing that sensitive operations are protected and auditable.

Before:

Limited control over what AI agents could do created security concerns. Organizations hesitated to broadly deploy AI tools due to compliance and audit requirements.

Now:

Granular permissions (read, write, run) and mandatory confirmations for high-impact operations provide enterprise-grade governance. Every action is traceable and controlled.

Documentation →

SEP 2, 2025

Accelerating time-to-value with templates

Beta Atlas AI

Ready-to-use agent templates like Data Scout and Time Series Trender reduce time-to-insight and empower engineers to self-serve.

Why is this valuable:

Pre-built templates eliminate the learning curve and setup time for common AI tasks. Engineers can start solving problems immediately without waiting on data science teams or learning complex configurations.

Before:

Setting up AI agents required deep technical knowledge and significant time investment. Each new use case meant starting from scratch, creating barriers to adoption.

Now:

Ready-to-use templates like Data Scout and Time Series Trender provide instant access to powerful AI capabilities. Engineers can explore data and analyze trends within minutes of starting.

Documentation →

SEP 2, 2025

Document parser enhancements

Beta Atlas AI

Parsing is smarter and more flexible. Users can leverage LLM vision capabilities, set custom parsing instructions, select page ranges, and extract multiple instances.

Why is this valuable:

Industrial documents contain critical structured data trapped in PDFs. Advanced parsing with LLM vision and custom instructions transforms these documents into queryable, actionable data.

Before:

Basic text extraction missed complex layouts, tables, and visual elements. Users had to parse entire documents even when only specific sections were needed.

Now:

LLM vision understands document structure including tables, charts, and handwriting. Custom parsing instructions adapt to any document format. Page range selection processes only relevant sections.

Documentation →

SEP 2, 2025

Checklist scheduling

Industrial Tools New Release

Create recurring schedules (daily, weekly, monthly) for any checklist directly in the app, removing dependencies on external schedulers.

Why is this valuable:

Routine maintenance and safety inspections require consistent execution on defined schedules. Built-in scheduling eliminates integration complexity with external systems and gives operators direct control.

Before:

Checklist execution relied on external schedulers or manual reminders. Setting up recurring tasks required coordination with IT teams and separate systems.

Now:

Operators create and modify recurring schedules directly in the checklist app. Daily, weekly, and monthly patterns are configured with simple controls.

Documentation →

SEP 2, 2025

Ad-hoc checklists from mobile templates

Industrial Tools New Release

With mobile checklist templates, operators can generate unique, ad-hoc checklists directly in the field with no dependency on desktop systems.

Why is this valuable:

Unplanned events and field observations often require immediate documentation outside standard workflows. Mobile template-based checklists empower field workers to capture critical data on-the-spot.

Before:

Ad-hoc inspections meant paper forms or unstructured notes. Creating digital checklists required desktop access and advance planning.

Now:

Select a template on your mobile device and instantly create a new checklist. Work offline in remote locations, data syncs when connected.

Documentation →

SEP 2, 2025

Activities visualization in CDM projects

Beta Industrial Tools

Charts now allows engineers to overlay activities (like maintenance or process events) directly on top of time series, bridging the gap between data anomalies and operational context.

Why is this valuable:

Understanding why sensor data shows anomalies requires operational context. Activities visualization creates a unified view where time series data and operational events coexist.

Before:

Engineers saw sensor anomalies in charts but had to check separate systems to find out what operational events occurred.

Now:

Activities appear as visual overlays directly on time series charts. See exactly when maintenance happened or when process changes occurred.

Documentation →

SEP 2, 2025

Smarter, faster ways to explore data

Industrial Tools New Release

View denser tables with frozen headers, resize preview panels, apply alphanumeric sorting, Enum filters, and "select all" options for faster navigation.

Why is this valuable:

Data exploration is a high-frequency activity where small friction points compound into significant time loss. Enhanced table controls and intelligent filtering transform routine data discovery.

Before:

Headers scrolled away in long tables, losing context. Fixed panel sizes forced constant scrolling. Manual sorting and filtering was tedious.

Now:

Frozen headers keep context visible. Resize panels to focus on what matters. Alphanumeric sorting finds items instantly. Enum filters and "select all" enable bulk operations.

Documentation →

SEP 2, 2025

Support for CDM and hybrid projects

Industrial Tools New Release

Hybrid CAD projects and CDM point cloud contextualization are now fully supported via API, accelerating the transition from classic to CDM.

Why is this valuable:

Organizations don't migrate to new architectures overnight. Hybrid project support enables gradual CDM adoption while maintaining existing CAD workflows.

Before:

Moving to CDM meant an all-or-nothing migration. Existing CAD projects couldn't mix with new CDM approaches.

Now:

Hybrid projects combine classic CAD with modern CDM data models seamlessly. Migrate at your own pace, project by project.

Documentation →

SEP 2, 2025

Automatic tag detection for 360° images

Industrial Tools New Release

Run text detection on 360° images to automatically generate annotation suggestions with bounding boxes, reducing manual work.

Why is this valuable:

360° imagery captures complete plant environments, but extracting equipment tags and labels has been painfully manual. Automatic text detection turns hours of annotation work into seconds.

Before:

Annotating equipment tags in 360° images required manual clicking and typing for every single tag. Large image sets took days or weeks.

Now:

Run automatic detection across your 360° image library. AI identifies text and suggests annotations with precise bounding boxes, 10x faster than manual annotation.

Documentation →

SEP 2, 2025

New measurement tools

Industrial Tools New Release

Enhanced 3D measurement tools: horizontal cylinder measurement, coordinate-based measurement, and improved UX for precision work.

Why is this valuable:

Dimensional verification, clearance checks, and retrofit planning require accurate spatial measurements without costly site visits.

Before:

Basic point-to-point measurements had limited capabilities. Measuring cylinders required approximations. No coordinate reference system.

Now:

Measure horizontal cylinders accurately with specialized tools. Use coordinate-based measurement for engineering-grade precision.

Documentation →

SEP 2, 2025

Power BI App 3D viewer

Beta Industrial Tools

View, rotate, and measure CAD models directly inside Power BI dashboards, correlating data with 3D spatial context.

Why is this valuable:

Power BI is the analytics platform of choice for millions, but industrial insights require spatial context. Embedding 3D models brings engineering reality to business dashboards.

Before:

Power BI showed charts and tables but lacked spatial context. Understanding where issues occurred meant switching to separate 3D viewers.

Now:

3D models appear natively in Power BI reports. Click equipment in the model to filter dashboard data. Rotate and measure directly in the report.

Documentation →

SEP 2, 2025

Extract information model from simulators

Beta Industrial Tools

Automatically extracts flowsheet hierarchies from simulator files into CDF. With initial GAP support, engineers can access this data without proprietary software.

Why is this valuable:

Simulator information models contain critical process engineering data locked in proprietary formats. Extracting this into CDF makes process hierarchies accessible to all stakeholders.

Before:

Engineers needed proprietary simulator software to view flowsheet structures. Process hierarchies were isolated from operational systems.

Now:

Flowsheet hierarchies automatically flow into CDF's data model. Any team member can explore process structures through standard CDF interfaces.

Documentation →

SEP 2, 2025

External dependencies in model revisions

Beta Industrial Tools

Upload smaller ZIPs and manage dependencies as separate CDF files, saving storage and making updates faster for large production networks.

Why is this valuable:

Large industrial models often share common dependencies across multiple revisions. Managing these as separate reusable files reduces storage costs and accelerates upload times.

Before:

Every model revision contained duplicate copies of dependencies, leading to massive ZIP files. Updates required re-uploading entire models.

Now:

Dependencies are stored once and referenced by multiple revisions. Upload only what changed — smaller, faster deployments.

Documentation →

SEP 2, 2025

Configurable tag detection UI

Beta Data Management

Fine-tune diagram parsing parameters (minTokens, searchField) and scope which assets or files are searched for more accurate results.

Why is this valuable:

Engineering diagrams vary dramatically across industries and plants. Configurable detection parameters let you adapt parsing logic to your specific diagram library.

Before:

One-size-fits-all detection parameters worked inconsistently across diagram types. No control over search scope.

Now:

Configure minTokens to filter out artifacts. Choose which fields to search. Scope detection to specific asset hierarchies or file sets.

Documentation →

SEP 2, 2025

Annotation box adjustments

Beta Data Management

Move and scale annotation boxes directly in the UI — even in bulk — saving manual rework when file versions change.

Why is this valuable:

Engineering documents evolve. When document versions change, annotation positions often need minor adjustments. Bulk editing transforms hours of repositioning into minutes.

Before:

When diagrams were revised, annotations were misaligned. Repositioning meant editing one by one. Bulk updates were impossible.

Now:

Select multiple annotation boxes and move or scale them together. Quick realignment preserves your annotation work across document revisions.

Documentation →

SEP 2, 2025

Core Data Model support for DB Extractor

Data Management New Release

The DB Extractor now writes directly into CDM instance spaces, simplifying database source onboarding and shortening time-to-value.

Why is this valuable:

Core Data Model represents CDF's future-proof data architecture. Native support in DB Extractor eliminates transformation middleware and reduces complexity.

Before:

DB Extractor only supported classic CDF resources. To use CDM, teams needed custom transformation pipelines and additional infrastructure.

Now:

DB Extractor writes directly into CDM instance spaces with native type support. Configure once and your database automatically populates your data model.

Documentation →

SEP 2, 2025

App-scoped access

Administration New Release

Admins can now scope access capabilities to specific applications, making queries in large Data Models faster and more efficient.

Why is this valuable:

Improves query performance in large Data Models by limiting scope. Maintains security while ensuring applications only access data they need.

Before:

Access capabilities applied globally across all applications. Large Data Model queries could be slow.

Now:

Scope access capabilities to specific applications. Queries are faster and more efficient by limiting evaluation to relevant app contexts.

Documentation →