New updates and improvements
V7 Go

We've created a new, unified panel for managing both your workspace-level files (Library tab) and integrations (Integrations tab), such as Google Drive. This centralized hub allows you to select all files or data sources for use as inputs or references inside your V7 Go projects.

• The Library is now a subsection within Knowledge Hub.

• The Library tab includes new search and sort functionalities for easier file management.

• When editing a prompt, you can inject and mention a file by typing @ or selecting it from the input list

• When selecting an empty File property inside a project, you can choose to:

  • Import a file from your computer

  • Use a file from the Library

  • Connect to Google Drive

At launch, Google Drive is the first available integration. More integrations are coming soon, and we're actively collecting user requests. If there's a specific integration you'd like to see, let us know by filling out this form.

V7 Go now supports Claude 3.7 Sonnet, Anthropic’s latest model with enhanced reasoning and coding capabilities. When selecting models and setting up your projects, you can now choose whether a specific V7 Go property should be calculated using standard Claude 3.7 Sonnet or Claude 3.7 Sonnet with thinking mode enabled for deeper analysis. This addition improves accuracy in instruction-following and multimodal understanding. It also provides greater flexibility and precision to optimize your AI workflows.

Reasoning models, from Deepseek to o3, have taken the world by storm.

Compared to traditional LLMs like GPT4o and Claude Sonnet 3.5, o3 has explicit step-by-step deduction baked into the training process, making it superior for tasks requiring complicated logical reasoning.

o3-mini can now power all property types in V7 Go, including Collections, Numbers, JSON and more.

In addition, we’ve added Gemini Flash 2.0, a powerful workhorse model with low latency and a large (1m) context window.

The Number Property enforces the output of numeric values, making it easier to work with data such as integers, percentages, and currency values.

Common prompts might be:

• Extract the revenue from @company in the @pitch deck. Include only the revenue for the last year. Output in $.

• What percentage of costs in the @CIM come from salaries?

• What is the net income in the @earnings report?

In addition, you can format decimals, negatives, separators, and alignment from the property configuration menu.

Stay tuned, as over the next few days, we’ll be adding both reasoning and AI citations to the Number Property.

Users can now recompute specific property values for individual fields without recalculating an entire property column. If a field produces an error or the output isn’t satisfactory, simply click on the field and select the Recompute option. You can also select a range of values, right-click, and recalculate multiple fields at once.

Until now, you could access and analyze web data in V7 Go by submitting specific URLs. With the new Web Search feature, it is now possible to ask questions directly in your prompt and pull in relevant information from the web.

• V7 Go will automatically use the most effective search queries and visit multiple pages.

• Perfect for data enrichment and accessing current information like stock prices.

• Get results as text, structured JSON, or Select/Multi-select properties.

Note: Source URLs and citations will be automatically displayed in the reasoning tooltip for full transparency in an upcoming update. In the meantime, include "list sources" in your prompt to view reference links in the output.

You can now upload Word documents directly into V7 Go without converting them to PDFs or CSVs. Use AI Citations, preview mode, and other functionalities with your Word documents just as you would with PDFs.

V7 Go supports both .doc and .docx formats.

Note: This feature requires new file properties created after this release.

You can now create collections within collections to get more granular insights into your data. This unlocks powerful workflows like splitting a PDF into pages as a top-level collection, then extracting structured metrics for each page in your nested collections.

With nested collections, you can still enjoy all the functionalities of standard collections, including filtering, AI data extraction, and dynamic references.