​

Collate AI Chat

Collate AI Chat is the conversational AI interface inside Collate. Ask questions about your data in plain language and Collate AI returns charts, insights, and answers — without writing SQL or knowing where the data lives. Collate AI Chat runs with your permissions, so every action it takes — querying data, editing metadata, creating tests — respects your access level.

​

Core Capabilities

Collate AI Chat connects directly to your organization’s knowledge graph — the layer built from your metric definitions, glossary terms, lineage, table schemas, and profiling data. This gives it accurate, organization-specific answers rather than generic approximations. Here’s what happens when you ask a question:

1. It finds the right definition first. If you ask about customer lifetime value, Collate AI Chat looks up your organization’s agreed-upon formula from the business glossary — not a generic approximation. Every teammate who asks the same question gets the same canonical answer.
2. It discovers the right tables and joins. Using lineage and schema metadata, Collate AI Chat figures out which tables to query and how to join them — including intermediate tables that aren’t obvious from the question.
3. It filters using real data. Column value filters come from profiler agent execution results — not guesses — so results reflect what’s actually in your data.
4. It shows its work. SQL queries appear inline as Collate AI Chat works through your question. You can see exactly what ran, which tables were used, and which definitions were applied.

​

What You Can Do

• Answer business questions: Ask in plain language — Collate AI Chat finds the right tables, joins, and definitions, then runs the query.
• Generate and show SQL: Every answer shows the SQL that ran, the tables used, and the definitions applied — so you can verify or hand it off to your data team.
• Build and refine charts: Bar, line, pie, donut, number, scatter, heatmap, and table charts — generated from your data and refined with follow-up prompts.
• Pin to dashboards: Save any chart to an AI Analytics dashboard for recurring use, scheduled refresh, and team delivery.
• Share conversations: Invite teammates as EDITOR or VIEWER so they see the same charts and reasoning and can continue the analysis together.
• Schedule reports: Deliver charts or dashboards via email or Slack on a recurring cadence.
• Explore assets: Browse and discover data assets from within Collate AI Chat without leaving the interface.
• Manage metadata: Create or edit glossary terms, assign owners, tag assets, and create data quality tests — from the chat.
• Manage your profile: Access your personal access tokens and connection settings directly from your Collate AI Chat profile.

​

Prerequisites

• Collate AI is enabled in your workspace. Contact your admin if you are unsure.
• Metadata, lineage, and usage ingestion jobs are running so Collate AI Chat has context.
• You have permissions to view and act on the assets you are asking about.

​

Use Cases

​

Data Analyst: Revenue Analysis

Ask a business question and Collate AI Chat finds the relevant certified tables, generates the SQL, and returns results with a chart.

• Prompt: “Give me total market share for eco vs non-eco products by revenue. Only Tier 1 data.”
• Result: Finds certified Snowflake tables (products, orders, customers), generates a join query, and returns the revenue split with a chart.
• Follow-up: “Use a donut chart with dark green for eco.” — Collate AI Chat updates the chart style and summary.

​

Data Analyst: Customer Segmentation

• Prompt: “What percent of customers bought eco products, grouped by customer tier?”
• Result: Produces SQL, groups by tier, and surfaces the insight that higher-tier customers engage more with eco products.

​

Data Steward: Glossary and Tagging

• Prompt: “Do we have a definition for revenue?”
• Result: Searches glossary terms and suggests creating one if missing.
• Prompt: “Create a term for revenue calculation and tag relevant Snowflake tables.”
• Result: Adds the term, links it to assets such as order_items, and records ownership.

​

Data Engineer: Lineage and Data Quality

• Prompt: “Show lineage for the customer report dashboard.”
• Result: Maps upstream tables (including customer_360) and downstream impacts.
• Prompt: “Search for anomalies in these tables: nulls, negatives, duplicates.”
• Result: Surfaces outliers such as negative unit_price values.
• Prompt: “Create test cases for the products table.”
• Result: Suggests completeness, uniqueness, range, and integrity tests and records who requested them.

​

Working with Charts

Ask a question and Collate AI returns results as charts automatically — no SQL, no BI tool, no configuration needed. Charts appear in the conversation as Collate AI works through your question.

​

Explore a Chart

Each chart has three views: Use the Chart Selector dropdown when Collate AI returns multiple charts for a complex question.

​

Customize a Chart

Use follow-up prompts to refine charts without starting a new conversation:

• “Use a donut chart instead.”
• “Break this down by region.”
• “Only show the top 10 results.”
• “Add a filter for Tier 1 data only.”

​

Pin to a Dashboard

Save useful charts to an AI Analytics dashboard for recurring use, scheduled refresh, and team delivery.

1. On any chart in the conversation, click Pin to dashboard.
2. Choose an existing dashboard or create a new one. Use the search box to find a dashboard by name quickly.
3. Open the dashboard from the AI Analytics page to see all your pinned charts.

Keep pinning charts from any conversation to build a complete picture over time. See AI Analytics to manage dashboards, schedule refreshes, and deliver reports to your team.

​

Share a Conversation

You can share any Collate AI Chat conversation with teammates — they open it and see the exact same charts, SQL, and reasoning you saw, and can keep asking questions right where you left off. To share a conversation:

1. Open the conversation you want to share.
2. Click Share on the conversation.
3. Enter the email addresses or user groups, set their role — Editor (can ask follow-up questions) or Viewer (read-only) — and click Invite.
4. Your teammate opens the shared chat and sees the same charts, SQL queries, and reasoning — not just a screenshot.

What teammates see when they open a shared chat:

• Every chart you generated, in the same order.
• The SQL query behind each chart — so they can verify the logic themselves.
• The AI’s reasoning steps — so they understand how the answer was derived.
• A live input to continue the analysis with their own questions (Editors only).

This applies to any conversation — not just ones with charts. Share an asset exploration, a governance workflow, or a data quality investigation just as easily.

​

Best Practices

• Be specific — include time ranges, owners, schemas, or tier levels to narrow results.
• Use follow-up prompts to refine charts rather than starting a new conversation.
• Review the SQL Collate AI Chat shows to confirm the query matches your intent before acting on the result.
• Pin useful charts to a dashboard and schedule a refresh so the numbers stay current without re-asking.
• Share conversations with teammates when collaborating so everyone sees the same charts and reasoning.
• Paste failing SQL or error context when asking for fixes so Collate AI Chat has what it needs to help.

​

Troubleshooting

• If answers seem incomplete, verify that recent metadata and lineage ingestion runs succeeded.
• If you cannot see certain assets, confirm your Collate permissions for those services.
• Collate AI responds in your UI language setting, not necessarily the language you typed your question in. To change it, click the Profile icon at the bottom of the left sidebar, then select Language.
• For inconsistent results, restate the question with the relevant schema or service name.
• For deeper issues — wrong formulas, wrong table surfacing, filters returning zero rows — see Improving AI Answers for catalog-level fixes.