Faraday is a prediction platform that provides on-demand customer context, delivering data through an API, MCP (Model Context Protocol), and a UI interface to power AI agents, personalized experiences, and smarter decisions.
[Purpose] Faraday is aimed at AI agents and business processes that need rich customer data to build modern customer experiences. It provides contextual data covering approximately 240 million U.S. adults, accessible through MCP, a real-time API, and batch deployment methods.
[Main Capabilities]
- Contextual data: Select the fields you need from more than 1,400 consumer and identity data points, and use them through the API, MCP, and file append methods. The data covers demographics, financial signals, lifestyle attributes, and behavioral indicators.
- Predictive models: Automatically build and deploy custom machine learning models using customers' own data, providing predictions such as propensity to convert, next best offer, churn propensity, and persona clustering.
- Data enrichment: Supports supplementing identity data (phone, email, address) for leads or customer lists, as well as enrichment with consumer information (demographics, financial signals, lifestyle, behavioral indicators).
- Audience analysis: Identify top segments and best customers through clustering analysis.
- Model builders: Provides a Propensity model builder (custom purchase propensity and churn propensity models) and a Recommender model builder (custom best recommendation models).
[How to Use]
- No-code dashboard: Upload data, configure predictions, and visually explore results through app.faraday.ai.
- REST API: Provides full documentation, supports batch deployment and real-time queries, returns enriched identity information and prediction scores, with response times under 200ms.
- Native MCP server: Allows AI agents to securely retrieve customer context within their context window.
- Native integrations: Directly connects to data warehouses (Snowflake, BigQuery, Redshift) as well as more than 50 downstream platforms such as Salesforce and Shopify.
[Data Sources] Faraday uses two data sources for predictions: one is the Faraday Identity Graph (FIG),Covers approximately 240 million U.S. adults and their households, including more than 1,400 consumer attributes, demographics, financial signals, lifestyle attributes, and longitudinal history; second, customer-owned records such as transaction, conversion, and interaction data. The two are matched through identity resolution, and after being merged, custom predictive models are built. During modeling, only data points relevant to customer outcomes are selected, rather than providing a raw data dump.
[Solutions and Applicable Scenarios] The two solutions are based on the same Faraday Identity Graph, with the same underlying data:
- Faraday Pro: Self-service, no contract or minimum spend required, pay per match, and 200 free credits upon sign-up. Suitable for users who already have customers or leads, mainly want to learn more information (demographics, financial signals, life stage, etc.), and are willing to select attributes themselves and call APIs. Supports real-time queries, file uploads, or data warehouse connections, and propensity and audience models can also be built in Pro. Supports MCP.
- Faraday Enterprise: A managed account that, on the same platform foundation, includes a dedicated context consultant to assist with activation, modeling strategy, and ongoing support. Suitable for complex use cases, such as building models and audiences based on complete event history, with annual partnerships. Supports MCP. Enterprise is sales-led and requires contacting sales to activate.
- Row Pro: If the goal is to obtain a direct mail list of strangers, that belongs to the separate product Row Pro.
[Integrations and Security] Faraday was founded in 2012 and processes PII (personally identifiable information) from thousands of U.S. brands, placing the security of consumer and customer data as a top priority.
[Customer Cases]
- John Hardy (jewelry brand): Uses on-demand data to instantly enrich customer profiles and achieve personalization.
- American Standard: Uses Faraday scores to prioritize high-value leads, increasing closed-won profit margin by 3x.
- Bespoke Post (subscription brand): Continuously scores customer characteristics based on product attributes, achieving 5x ROI, a 5% increase in revenue per customer, and a 3% reduction in churn.
- Bee's Wrap: Combines sales data with Faraday context to generate audience profiles and customer insights, successfully securing placement in 550 Target stores.
- Boll and Branch: Uses audience profiles generated by Faraday to send the best creative versions, increasing email conversion rate by 30%.
[Limitations] The materials do not provide specific pricing, cost details beyond the free credits, data coverage regions (only U.S. adults are mentioned), model accuracy, or compliance certifications.
