# Prophecy at Snowflake Summit 2026

June 1-4 | Moscone Center | Booth #1006

Introducing Prophecy Agentic AI | Founders Demo the Future of Data Workflows - YouTube

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[Introducing Prophecy Agentic AI | Founders Demo the Future of Data Workflows](https://www.youtube.com/watch?v=0POItQz1OWc) [Prophecy - Agentic Data Prep & Analysis](https://www.youtube.com/channel/UCSx4n8fdysmA30Q5OiS2kYQ)

## Agentic Data Prep & Analysis on Snowflake

## Your data stack is modern. Your workflow for building on it isn't. Let's fix that.

Join us at Snowflake Summit in San Francisco.

We bring the power of Claude Code to your Business Data Users. Use AI agents to build visual data workflows with governance and scale on Snowflake.

## How Prophecy Works

Prophecy Agentic AI Demo: From Campaign Data to Smarter Marketing Decisions - YouTube

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[Prophecy Agentic AI Demo: From Campaign Data to Smarter Marketing Decisions](https://www.youtube.com/watch?v=EAP7Rson3bI) [Prophecy - Agentic Data Prep & Analysis](https://www.youtube.com/channel/UCSx4n8fdysmA30Q5OiS2kYQ)

1. User describes business goal to agent
2. Agent generates a workflow to prepare the data, user refines
3. Agent generates insights from the prepared data

Preparation

### How Agentic Data Prep & Analysis Works

**Phase 1 – Preparation:** The user describes a business goal in natural language (example: "segment marketing leads by campaign"). The AI agent reads the knowledge graph, thinks through the logic, and writes a data pipeline. Intermediate steps visible to the user include joins, filters (e.g. "status = new"), and segment definitions against account detail data.

**Phase 2 – Review:** The agent surfaces its work as a visual pipeline that the user can inspect step by step — showing exactly how the data was prepared, what was joined, and what was filtered. Users can refine any step before proceeding.

**Phase 3 – Analysis:** Once the prepared data is validated, the agent generates insights and visualizations. Example output: "There are 3 segmentations of the marketing leads with interesting insights." Results are rendered as charts and summaries the user can act on immediately.

Analysis

There are 3 segmentations of the marketing leads with interesting insights. Let’s visualize them below:

**Demo: AI agent workflow in action.** A user types the prompt: "segment marketing leads by campaign." The Prophecy AI agent immediately begins working: it reads the Knowledge Graph to understand available data, thinks through the required logic, and writes a data pipeline. The pipeline joins the open leads table with account detail data, applies a filter for status = new, and segments the results by campaign. Once complete, the agent responds: "There are 3 segmentations of the marketing leads with interesting insights" and renders them as visualizations for the user to review.

## SPEAKING SESSIONS

### Prophecy: AI Agents Driven Data Prep for Analysts

AI agents accelerate data preparation and analysis; we’ll show what they can do. They let business data teams move faster, boost productivity, and deliver results without relying on data engineering—all under strong governance on your cloud data platform. We’ll close with practical change management steps for moving off desktop data prep.

## Meet our Leadership Team

Raj Bains

Founder CEO

Maciej Szpakowski

Co-Founder

Edan Kabatchnik

Senior VP, Products

Vikas Marwaha

Co-founder

Jordan Markham

VP, Customer Success & Support

Sandra Chim

VP, Marketing

## Book a Meeting at Summit

Want to see it in action? Book a meeting with our team to learn how Prophecy is shaping the future of data with AI.

Let’s get connected!