AWS re:Invent 2025 - EverCommerce’s Secret to AI-Ready, Multi-Brand Data (ANT101)

Summary of AWS re:Invent 2025 - EverCommerce's Secret to AI-Ready, Multi-Brand Data (ANT101)

Introduction to Fiverr and EverCommerce

• Fiverr is a data ingestion and data movement company focused on automated, secure, and scalable data movement
• Fiverr has a broad portfolio of over 700 pre-built connectors for SaaS applications, operational data stores, and other data sources
• Fiverr serves over 7,000 customers globally, including EverCommerce

EverCommerce's Data Modernization Journey

• EverCommerce is a leading service commerce platform that provides SaaS solutions to over 700,000 small business customers across 40+ countries
• When Kalpit Patel, VP of Enterprise Data, joined EverCommerce 18 months ago, the company had a highly decentralized data landscape with data silos across its 50+ independently operated brands
• Key challenges included:
  • Lack of data organization and centralization
  • Difficulty providing data accessibility and self-service to the business
  • Need for robust data governance, especially as the company looked to leverage AI and ML

Leveraging Fiverr's Managed Data Lake Service

• To address these challenges, EverCommerce partnered with Fiverr and leveraged their Managed Data Lake service built on AWS S3
• This allowed EverCommerce to:
  • Ingest and consolidate data from disparate sources into a centralized, governed data platform
  • Provide self-service access and reporting capabilities to the business
  • Lay the foundation for advanced analytics and AI/ML initiatives

Building an "AI-Ready" Data Factory

• EverCommerce's goal was to create a "data factory" that could enable the business and its customers, rather than just a centralized data platform
• Key aspects of this data factory include:
  • Leveraging Fiverr's integrations with tools like dbt to automate data quality and "shift left" governance
  • Incorporating reverse ETL capabilities from Census to enable bi-directional data flows and better serve business users
  • Designing the architecture to be "AI-ready", with the ability to run sophisticated ML models across the consolidated data

Business Impact and Future Plans

• The data factory has provided EverCommerce with:
  • Improved cross-brand visibility and the ability to drive enterprise-level reporting and analytics
  • Enhanced customer intelligence and the ability to deliver more personalized experiences through AI/ML
  • Accelerated time-to-value and reduced operational overhead compared to building the solution in-house
• Looking ahead, EverCommerce plans to further leverage the Fiverr ecosystem, including the recent Fiverr-dbt integration, to continue automating and scaling their data capabilities.
• The ultimate goal is to enable data monetization and deliver API-based data services to EverCommerce's small business customers, empowering them with data-driven insights.