What New: Account ID and Account Number are now available as dimensions for Bing Ads in the NinjaCat. You can find them under the names of External Account ID and External Account Number.

Two new dimensions: Targeting Type and Targeting Value are now available in Pinterest Ads. These fields come from Pinterest's targeting_analytics endpoint, allowing you to break down campaign performance by targeting segment directly within NinjaCat.

As part of bringing in this new endpoint, 90+ existing Pinterest metrics (impressions, clicks, spend, conversions, video views, ROAS, and more) have also been mapped to the targeting-level breakdown, giving you a comprehensive view of how each targeting strategy is performing.

What's New?: The "Search Term" and "Search Term Match Source" dimensions are now available in NinjaCat for Google Ads Performance Max campaigns, allowing you to analyze search term performance data in our reporting interface.

What this means for you: If running Performance Max campaigns can now:

• Select "Search Term" and "Search Term Match Source" as dimensions in Google Ads reports
• View search terms attributed to Performance Max campaigns alongside advertiser-provided keywords

We're excited to announce that we've added support for Local Service Ads (LSA) within our Google Ads API provider integration.

With this update, you can now access and report on Local Service Ads data directly within the platform. As part of this enhancement, we've introduced several new LSA-specific dimensions to provide greater visibility and flexibility in your reporting.

We have introduced a new field "Agent Directions" for Datasets. This enhanced method of getting details to the agent about your dataset should be more scalable than our past method (just the dataset description field at the agent level).

Navigation Path: Data Cloud --> Datasets --> Select Dataset --> Agent Directions field in right hand panel --> Pencil Icon

Information added here should explain what this dataset is, any important information about the fields within the dataset and anything else that will always be applicable to this dataset no matter which Agent its assigned to. This description will basically 'follow' the dataset to any Agents it gets assigned to and will help the Agent understand when and how to use it during user convos.

At the Agent level, you'll see this description pull through, and there's also an "Additional Agent Directions" field where additional directions can be optionally inserted that may only be applicable for this agent.

Note that this is currently only available for the original ingested dataset as well as SQL Transform datasets, but is not yet available for Views (but will be coming soon).

Every data app save now creates an automatic version snapshot. Access full version history and restore any previous version with one click.

How to Use:

Click "Version History" in the Data Apps Builder to view, preview, and restore previous versions.

Available now for all data apps

As of Jan 15th, we've extended our list of supported file types that Agent's can handle (both in the agent's knowledge as well as uploaded directly in the conversation). Agents can now also read any "text" file—meaning files with mime type text/*. This includes but is not limited to: .csv, .htm, .html, and .py files.

View the full list of supported files here: https://docs.ninjacat.io/docs/adding-data

First, some context: Files uploaded to an Agent's Knowledge are only inserted into conversations / the context window when needed. Which is good, so that we avoid burning through the limited context window just from all the uploaded files, but we want to make sure that files are used when they should be. Previously, Agents only had filenames to decide which files to use, which sometimes led to missing or incorrect file selection.

New Feature: File Descriptions are now auto-generated for all newly uploaded files (as of the release a few hours ago). Agents now use both filename and description to determine when to insert files into conversations. This should help ensure the right files are used at the right time.

Note: Files uploaded before this release will have a description field available, but it must be manually added.

More info: https://docs.ninjacat.io/docs/adding-data

For the first time, we're now offering models from Google as model options for Agents: Gemini 3 Pro and Gemini 3 Flash.

Why these models are a big deal: -Massive 1M Context Window: While our current Anthropic models are great for reasoning, Gemini's 1-million-token context window is a game-changer. For those scenarios where you're consistently running into context window max, try switching to a Gemini model. -Low Cost Profile: These models offer a significantly lower price point, especially for high-volume tasks. Gemini 3 Flash is particularly optimized for scale, coming in at just $0.50 per 1M tokens—making it our most cost-effective option for speed and scale.

Our Model Selection documentation has been updated with this information here: https://docs.ninjacat.io/update/docs/model-selection

You can now programmatically monitor dataset ingestion health using the NinjaCat Management API. This feature provides visibility into when dataset ingestions fail, return no data, or are delayed, helping teams identify and respond to issues before they impact reporting or users.

With the new Ingestion History / Batches endpoints, you can:

• Query recent ingestion runs across datasets
• Identify failed, incomplete, or in-progress ingestions
• Review batch-level outcomes and totals
• Drill into execution-level error details, including credential and permission issues

This capability is designed to support a variety of workflows, including scheduled health checks, custom monitoring scripts, and automated alerts using various tools. Teams can choose how frequently to check ingestion status and which datasets are most important to monitor.

To get started, provide your Management API credentials and call the ingestion history endpoints with supported filters (for example, checking the last 24 hours for errors or no-data responses). When issues are identified, remediation—such as fixing credentials, updating permissions, or running backfills—is handled directly in the NinjaCat UI.

Documentation can be found here: https://documenter.getpostman.com/view/4308783/SVSGMpwr#91ec4a09-c561-4287-bdf2-c14988c9412b