Customer context platform providing predictive insights and propensity scoring for AI.
What it does
Enriches first-party CRM and warehouse data with over 1,500 responsibly sourced consumer attributes.
Builds automated propensity, lifetime value, and persona cluster models to forecast buyer behaviors.
Delivers real-time predictions directly into CRMs, ad channels, and AI agents via API and MCP.
Includes built-in ethical AI controls to detect and mitigate demographic bias in predictive scoring.
Why it works
Deterministic coverage of 240 million US adults provides deep consumer signals beyond simple web clicks.
Automated decision-tree and cluster modeling delivers turn-key predictive scoring without custom ML engineering.
Model Context Protocol (MCP) integration optimizes context budgets for AI agents without prompt bloat.
Built-in bias mitigation and explainable AI metrics ensure regulatory compliance and fair consumer targeting.
Customer context platform providing predictive insights and propensity scoring for AI.
Overview
Faraday is a customer context and predictive intelligence platform that enables consumer-facing brands, marketers, and AI agents to forecast customer behavior. Powered by the Faraday Identity Graph of 240 million US adults, it enriches first-party data with 1,500+ real-world consumer attributes. The platform generates custom predictive models for propensity to convert, lifetime value, persona clustering, and next-best offers. With native integrations for CRMs, data warehouses, and Model Context Protocol (MCP), Faraday grounds AI agents in real-world data.
Popularity:Serves hundreds of consumer brands and manages data on 240M+ US adults
HQ:Burlington, Vermont, United States
Status:Active
Funding status:Funded
Customer type:B2B
Funding:$11.2M
Pricing:Subscription
Tech stack:Python, React, Node.js, PostgreSQL, Google BigQuery, Docker, Kubernetes
Platform:Web
Integrations:HubSpot, Salesforce, Snowflake, Google BigQuery, Klaviyo, Meta Ads, Google Ads, Zapier, CARTO
What it does
Enriches first-party CRM and warehouse data with over 1,500 responsibly sourced consumer attributes.
Builds automated propensity, lifetime value, and persona cluster models to forecast buyer behaviors.
Delivers real-time predictions directly into CRMs, ad channels, and AI agents via API and MCP.
Includes built-in ethical AI controls to detect and mitigate demographic bias in predictive scoring.
Who it's for
E-commerce & Retail Brands
Financial Services & Fintech Companies
Home Services & Direct-to-Consumer Businesses
Growth Marketers & Data Science Teams
Why it works
Deterministic coverage of 240 million US adults provides deep consumer signals beyond simple web clicks.
Automated decision-tree and cluster modeling delivers turn-key predictive scoring without custom ML engineering.
Model Context Protocol (MCP) integration optimizes context budgets for AI agents without prompt bloat.
Built-in bias mitigation and explainable AI metrics ensure regulatory compliance and fair consumer targeting.
Founder story
Faraday was founded in 2012 in Middlebury, Vermont, by Andy Rossmeissl, Robbie Adler, and Seamus Abshere. Having previously co-founded sustainability platform Brighter Planet, the founders set out to help residential solar providers identify high-propensity buyers. After receiving an initial grant from the US Department of Energy, they built an ethical consumer modeling engine and relocated to Burlington, Vermont, expanding the platform across retail, finance, and enterprise SaaS verticals.
Alternatives
Comparison overview
Faraday combines first-party CRM data with an ethically sourced Identity Graph of 240M US consumers.
Delivers predictive propensity and persona scores directly via APIs and MCP for AI agent grounding rather than relying solely on past clickstream history.
Includes native algorithmic bias detection and mitigation tools designed to prevent demographic discrimination in predictive modeling.