01
Describe the tool categories
Tell Kollab which AI tool categories you care about, such as text generation, image generation, or coding assistants, and define fields like pricing, features, use cases, and team feedback.
Build an AI tool library
Let Kollab search, compare, and track AI tools your team has tried, then write the structured library into Notion and adjust it with natural language.
Built for product teams, operations teams, and technical leads who need to follow AI tool changes and decide which tools are worth adopting. It is especially useful when teammates have tried different tools, but evaluations and comparisons are scattered across Slack and personal notes.
Help me build an AI tool tracking database in Notion. Start with two categories: text generation and image generation. Track these fields: tool name, official website, pricing model, core features, best-fit use cases, and whether our team has tried it.
Search for the current top 5 tools in each category and fill them in. Then check whether anyone discussed these tools in our Slack #tools-and-resources channel, and add that feedback too.
How the workflow runs
Read through the workflow once, then swap in your own roles, sources, and outputs.
02
Search and populate the database
Kollab searches the web for mainstream tools in the category, captures official pricing, feature highlights, and reviews, then writes them into Notion.
03
Merge real team feedback
The Slack Connector extracts tool experiences and opinions teammates have shared in channels, then attaches them to the matching tool entries.
04
Keep evolving the library
Use natural language any time to add categories, add comparison fields, filter by scenario, or ask Kollab to search and append new tools.
Manual workflow vs Kollab
Turn tool discovery, team feedback, and Notion database maintenance into one workflow that can keep updating.
| Manual workflow | With Kollab | |
|---|---|---|
| Collect tool information | Search official sites and reviews one by one, often taking hours | Searches automatically and writes structured entries |
| Collect team feedback | Ask teammates if they have tried each tool and record answers manually | Extracts usage feedback from Slack automatically |
| Maintain and update | Check manually on a schedule, and the data gets stale easily | Add new tools with one natural-language request |
| Compare and decide | Open a spreadsheet and fill every field by hand | Filter and sort directly in the Notion database |
| Total time | Half a day to set up, high maintenance cost | Minutes to set up, one message to update |
How it works
From category definition to Notion delivery, Kollab connects public research, team feedback, and database structure in one workflow.
01
User describes tool categories and tracking fields
02
Kollab searches the web for tool information
03
Slack Connector extracts team usage feedback
04
Structured data is written into Notion
05
The user can append or adjust it later with natural language
Build this workflow with Kollab
Follow the related capability pages to see which product layers and tools make this use case repeatable for a team.
Build your AI tool library with one request
Let Kollab handle search, comparison, and tracking.
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