Meet Salesforce Genie

No, not that kind of genie. Salesforce Genie is a real-time hyperscale data platform that enables the delivery of personalized and individualized experiences across sales, marketing, service and commerce. Genie, which runs on Hyperforce brings hyperscale, real-time data – optimized for engagement, optimized for analytics, optimized for AI — deeply connected into the Salesforce platform. But wait, why is this different and/or better than the old way of integrating data through the Force.com platform that’s been around since ~2008? Genie is a completely different architectural and procedural approach to ingesting, harmonizing, sharing and automating data. The old platform approach to data integration was based on transactional data stored in a traditional relational database. Genie uses a data lake to store the data. this opens up several important capabilities. The data lake is based on the lakehouse architecture and has the ability to “learn” Salesforce metadata model, which is the method that all services in Salesforce interact.

First, what is data lakehouse architecture? A lakehouse is a hybrid approach that combines a data lake with the data structures and management capabilities that existed in the older approach to data storage, data warehouses. This hybrid architecture has many advantages and includes:

  1. Open standards of data storage formats that enable other data stores like warehouses and lakes, services like machine learning (ML) to directly exchange data in both directions through open storage formats without copying data

  2. Data diversity by supporting both structured and unstructured data types

  3. Robust governance with compliance built-in, data lineage, consent mapped to models means system can maintain data integrity

  4. Direct data access for BI tools and support for data science tools, artificial intelligence (AI) / ML

  5. Real-time data streaming

Because of this modern approach to the data lake, Genie has the ability to integrate to any outside services and data repositories like the announced Snowflake integration. It also opens up a myriad of automation capabilities in Salesforce Einstein AI and Salesforce Flow. The architecture opens up the power of real-time and/or near real-time data streaming, which creates a much more complete and usable customer data graph.

If this all sounds a bit like a customer data platform (CDP) to you, you wouldn’t be wrong. It takes the CDP paradigm and extends it beyond marketing into all parts of the CX suite from sales to service. The real-time and near real-time streaming capabilities across the entire CRM / CX suite of applications enables a broad set of automation capabilities and process workflows. This new data foundation for the business creates the ability to have a complete and actionable customer data graph that supports a universal CX strategy.

Michael Fauscette

High-tech leader, board member, software industry analyst, author and podcast host. He is a thought leader and published author on emerging trends in business software, AI, generative AI, agentic AI, digital transformation, and customer experience. Michael is a Thinkers360 Top Voice 2023, 2024 and 2025, and Ambassador for Agentic AI, as well as a Top Ten Thought Leader in Agentic AI, Generative AI, AI Infrastructure, AI Ethics, AI Governance, AI Orchestration, CRM, Product Management, and Design.

Michael is the Founder, CEO & Chief Analyst at Arion Research, a global AI and cloud advisory firm; advisor to G2 and 180Ops, Board Chair at LocatorX; and board member and Fractional Chief Strategy Officer at SpotLogic. Formerly Michael was the Chief Research Officer at unicorn startup G2. Prior to G2, Michael led IDC’s worldwide enterprise software application research group for almost ten years. An ex-US Naval Officer, he held executive roles with 9 software companies including Autodesk and PeopleSoft; and 6 technology startups.

Books: “Building the Digital Workforce” - Sept 2025; “The Complete Agentic AI Readiness Assessment” - Dec 2025

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