Q4 2025 Product Release: Delivering Faster Troubleshooting, Higher Data Quality, and Full-Scale Optimization

Problem

Solution: What You Can Do Now

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

Instant Flow Tracing: The canvas is now cleaner. Hover over any connection path to instantly highlight that specific flow, increasing user efficiency when troubleshooting.

Problem

Solution: What You Can Do Now

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

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

Problem

Solution: What You Can Do Now

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

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

Problem

Solution: What You Can Do Now

Manual Measuring: Measuring basic dimensions like pipe diameters was laborious.

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

Problem

Solution: What You Can Do Now

Manual Tweaking: Hardcoded default 3D settings forced users to manually adjust them per session.

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.

Problem

Solution: What You Can Do Now

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

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.

Problem

Solution: What You Can Do Now

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

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

Problem

Solution: What You Can Do Now

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

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

Problem

Solution: What You Can Do Now

Incorrect Asset Links: Operators struggled to attach the correct asset to field observations, reducing data quality.

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.

Problem

Solution: What You Can Do Now

Trial-and-Error: Complex definitions made subtle errors difficult to find, leading to a frustrating configuration.

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

Problem

Solution: What You Can Do Now

Hidden Triggers: Managing live pipelines was risky without clear visibility into automated starting points.

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

Problem

Solution: What You Can Do Now

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

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.

Problem

Solution: What You Can Do Now

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

Dedicated Review Workflow: The UI tabs are split into four distinct sections, with the first tab dedicated solely to reviewing annotations. This allows users to verify or reject file and asset annotations individually or in bulk and enables annotation management across multi-page files, significantly improving focus and workflow efficiency.

Problem

Solution: What You Can Do Now

Wasted Resources: Transformations often re-process and re-write large amounts of identical data, wasting compute resources and masking optimization opportunities.

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.

Problem

Solution: What You Can Do Now

Blind Deployment: Lack of visibility into agent performance or failures made it hard to build trust or troubleshoot.

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.

Problem

Solution: What You Can Do Now

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

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

Problem

Solution: What You Can Do Now

Poor Japanese Search: The existing search didn't account for the unique structure of Japanese, leading to poor relevance.

Morphological Analysis: Enhanced search capability uses Morphological Analysis to provide relevant results, balancing precision and recall.