Lists

Structured data tables with AI-powered enrichment and processing

Lists are structured, AI-powered data tables that let you organize information in rows and columns and then process it at scale with your AI agents. Build custom data grids, upload existing spreadsheets, and let AI enrich every row with research, analysis, and insights — automatically.

From Spreadsheets to Smart Data: Upload a CSV of 200 target companies, assign an AI agent, and have every row enriched with company overviews, decision-maker contacts, tech stack details, and qualification scores — all in minutes.

Overview

Lists combine the familiarity of spreadsheets with the power of AI agents. Each list is a fully customizable data table where you define columns — including AI-enabled columns that are automatically populated by your agent when rows are processed.

Feature	Capability	Business Impact
Typed Columns	Text, Number, Boolean, and Date and Time columns	Sorting, filtering, and math that behave correctly
AI Enrichment	AI agents research and fill columns automatically	Eliminate hours of manual data entry
Templates	Start from pre-built templates or create your own	Get started in seconds with proven structures
Bulk Upload	Import CSV or Excel files up to 10,000 rows	Bring existing data into the AI pipeline
Filter, Sort & Pivot	Query and summarize on the server, not in your browser	Large lists stay fast to work with
Real-Time Processing	Watch AI process rows live with status updates	Full visibility into enrichment progress
Team Sharing	Share lists with Owner, Editor, or Viewer permissions	Collaborate on data across your organization
Export	Download enriched data as CSV	Move results into your existing tools

How Lists Work

Step	What Happens	Your Action
1. Create	Start a blank list or select a template	Name your list and choose a starting point
2. Columns	Define what data you want to collect and enrich	Add columns, mark some as AI-enabled with prompts
3. Add Data	Populate the list with rows manually or via file upload	Type entries or upload a CSV/Excel file
4. Assign Agent	Select which AI agent will process the list	Pick from your organization's agents
5. Process	AI researches and fills each AI-enabled column per row	Click Process and monitor real-time progress
6. Review	Inspect enriched data, filter, and export	Download results or continue refining

Use Cases

For Users

• Sales Prospecting: Upload a list of target companies and have AI research each one — generating overviews, identifying decision makers, and scoring fit

• Vendor Evaluation: Create a vendor comparison grid with AI-powered research on pricing, features, and market position

• Market Research: Build lists of companies in a target segment and let AI enrich them with firmographics, tech stack, and growth signals

• Account Planning: Maintain enriched account lists with up-to-date intelligence on customers and prospects

• Competitive Analysis: Track competitors with AI-populated columns for product updates, funding, and strategic moves

For AI Agents

• Lead Qualification: Agents research each lead using web search, tech stack inspection, and CRM lookups to qualify or disqualify automatically

• Data Enrichment: Agents visit company websites, analyze public data, and fill structured columns with validated information

• Opportunity Scoring: Agents evaluate rows against custom criteria and produce qualification scores

• CRM Synchronization: Agents pull data from connected CRMs (Salesforce, HubSpot) to enrich rows with existing customer data

• Bulk Submissions: Agents process and submit enriched rows to external systems like AWS Partner Central

Creating a List

1

Navigate to Lists Click Lists in the sidebar to open the Lists home page.

2

Click "New List" Choose to create a blank list or start from a template. Give your list a name and optional description.

3

Define Your Columns Add columns to define the structure of your data. Mark columns as AI-enabled and provide prompt templates to tell the agent what to research. Learn more about columns →

4

Add Rows Manually add rows one at a time, or use Add data to upload a CSV/Excel file of up to 10,000 rows.

5

Assign an AI Agent Select which agent should process the list. The agent's instructions, personality, and MCP integrations will be used during processing. Learn more about changing agents →

6

Process and Review Click Process to start AI enrichment. Monitor progress in real time, then review, filter, and export your enriched data.

Data Management

Adding Rows

Method	Description	Best For
Manual Entry	Add rows one at a time through the table UI	Small lists or individual additions
CSV Upload	Import a .csv file with headers mapped to your columns	Migrating existing spreadsheet data
Excel Upload	Import .xlsx or .xls files	Bringing in formatted workbooks
Ask Darcy	Open chat from the list and ask her to add or update rows	Research-driven additions

Row Operations

• Edit: Double-click a cell to edit its value in place

• View Details: Single-click a cell to open the row detail panel and see every column at once

• Delete: Remove individual rows, or select several and use Delete Rows

• Reprocess: Re-run AI enrichment on selected rows, or on the whole list

• Export: Download rows as CSV — everything, or just the complete or failed ones

Upload Limits

Constraint	Limit
Max Rows	10,000 per file
Max File Size	25 MB
File Formats	.csv, .xlsx, .xls
Replace Mode	Optionally replace all existing rows on upload

Replace existing rows deletes every current row and adopts the file's column structure. It can't be undone.

Finding & Summarizing Data

Search, filters, and sorting run on the server, so a list with thousands of rows stays responsive — rows load in pages of 200 rather than all at once. The Pivot view summarizes your data with Count, Sum, Average, Min, and Max.

See Filtering, Sorting & Pivots for the details.

Sharing & Permissions

Control who can access and modify your lists:

Permission	Capabilities
Owner	Full control — edit, process, share, delete
Editor	Add/edit rows, add/edit columns, process rows
Viewer	View list data, export

Share lists with individual users or with Groups for bulk access management.

Integration with Other Features

Agent Integration

• Lists use your configured Agents to process rows

• Agents bring their custom instructions, MCP tools, and integrations

• Switch agents at any time to change processing behavior

MCP Integration

• Agents with MCP integrations can access external systems during row processing

• Connected CRMs, databases, and APIs are available as enrichment sources

Chat Integration

• Open chat from inside a list and Darcy can query it, add rows, and make bulk updates on your behalf

• Chat uses the list's assigned agent, so its instructions and integrations apply

• Reading and inserting rows happen directly; updating or deleting rows asks for your approval first

Best Practices

Practice	Recommendation
Start with a template	Use built-in templates to get a proven column structure, then customize
Limit AI columns	3–5 AI-enabled columns per list gives the best balance of speed and depth
Write clear prompts	Specific column prompts produce better AI results than vague instructions
Test with small batches	Process 5–10 rows first to validate column prompts before running a full list
Choose the right agent	Assign an agent whose instructions and tools match the list's purpose
Use upload for volume	CSV/Excel upload is faster than manual entry for anything over 10 rows

Pro Tip: Combine AI-enabled columns with manual columns. Use manual columns for data you already have (company name, website) and AI columns for data you want the agent to research (company overview, tech stack, decision makers).

Next Steps

Goal	Documentation
Learn about column types and setup	Columns & Configuration
Filter, sort, and summarize data	Filtering, Sorting & Pivots
Process rows with AI agents	Processing Rows with AI
Use pre-built list templates	List Templates
Learn about AI agents	Agents