Faraday

Faraday is a customer context platform designed to deliver on-demand, real-time data about individual consumers directly into AI agents, workflows, and business applications. The platform compiles and maintains a graph of over 240 million U.S. adults, linking each person to more than 1,500 consumer and identity data points sourced from top-tier data compilers. These data points cover demographics, behavioral attributes, purchase intent, life events, household composition, location history, financial indicators, and digital engagement signals, among others. Faraday exposes this contextual data through three primary delivery methods: a real-time API for low-latency lookups, the Model Context Protocol (MCP) for integration with large language models and agentic systems, and batch file appends for periodic enrichment of existing customer records. Users can select exactly which data elements they want included in each payload, tailoring the context to specific use cases such as personalizing e-commerce recommendations, scoring leads, targeting marketing campaigns, segmenting audiences for retention programs, or grounding AI chatbots with verified customer details. The platform’s underlying identity resolution engine, which Faraday calls the Faraday Identity Graph (FIG), has been overhauled to version 2 to improve matching accuracy across disparate data sources, deduplication, and time-series tracking of consumer changes. Business teams can configure workflows through a web interface or programmatically via SDKs and a RESTful API. Faraday also provides pre-built templates for common scenarios like customer 360 enrichment, predictive churn models, and next-best-action triggers. The system is designed for enterprises and startups that need to inject granular, permissioned consu