Customer context and predictions for AI agents, marketing teams, and customer workflows.
Faraday is a customer context platform that combines consumer and identity data with a company's own customer records. It helps teams understand individuals and households, predict customer behavior, and deliver that context to AI agents and business applications.
Teams can select attributes for on-demand enrichment or build custom models using their own data. Results are available through real-time APIs, MCP connections, file enrichment, and recurring deployments. A dashboard supports segment comparisons, persona analysis, and reporting.
Resolve identities and enrich customer or prospect records with more than 1,400 consumer and identity attributes, including contact information, demographics, financial signals, lifestyle attributes, and behavioral indicators.
Train propensity models for conversion, churn, and repeat purchase, plus recommenders for products, content, or locations. Faraday automatically engineers predictors from first-party data, including time, frequency, and value measures.
Define populations using traits and behavioral events, cluster customers into personas, and compare segments to understand their characteristics.
The Enterprise MCP server lets compatible agents connect data, define cohorts, train models, and deploy context through natural-language instructions. Pro has a separate MCP server for person lookups and project management.
Deliver context to warehouses, CRMs, email platforms, files, APIs, and custom webhooks. Supported data connections include Snowflake, BigQuery, Postgres, S3, HubSpot, and Salesforce.
Review model performance, feature importance with directionality, and technical reports. Faraday describes its models as cross-validated and explainable, with optional bias management.
Sales and lead acquisition teams can rank prospects by likelihood to convert, reorder engagement queues, and suppress low-priority leads from costly direct mail campaigns.
Retail and subscription teams can deploy next-best-offer predictions into email workflows to select relevant products, bundles, or promotional discounts for each customer.
Customer engagement teams can identify customers at risk of churn and use repeat-purchase readiness predictions to decide whom to contact and when.
Expansion teams can size and map an addressable market across a geography, using consumer context to evaluate potential areas for growth.
Pro is self-service, with payment per match and no contract or minimum. It supports enrichment plus propensity and persona models. Enterprise adds a dedicated context consultant for activation, modeling strategy, and ongoing support through an annual engagement. Both use the same underlying identity graph.
You need an existing Faraday account and an MCP-compatible client. Enterprise connects at https://mcp.faraday.ai/mcp using browser-based OAuth. Pro uses https://api.pro.faraday.ai/v1/mcp; its projects are separate from the Enterprise server.
Faraday supports enrichment using personally identifiable information to match people with built-in consumer data. Teams can also connect customer traits and behavioral event streams for models based on their own data.
Faraday advertises 200 free credits when signing up for Pro. Pro users choose attributes and access matching data through real-time lookups, file uploads, or warehouse connections.
Traffic data is for reference only.
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