Faraday
Faraday is an AI-driven platform that focuses on predicting customer behavior. It integrates with existing business stack to facilitate data-driven decision mak...
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What is Faraday?
Faraday is a customer context platform that provides on-demand customer data via API, MCP (Model Context Protocol), and UI to power AI agents, personalized experiences, and smarter business decisions. Founded in 2012 and headquartered in Burlington, Vermont, Faraday enables consumer brands, marketing agencies, and AI platforms to access the Faraday Identity Graph (FIG), which contains over 1,500 data points on approximately 240 million U.S. adults and their households.
The platform combines first-party customer data with third-party consumer data including demographics, financial signals, property details, and lifestyle attributes to build custom predictive machine learning models. Key features include propensity modeling (likelihood to convert, churn, or buy), next best offer recommendations, persona clustering, identity resolution, bias detection and mitigation, prediction explainability, real-time API with sub-200ms response times, batch deployment, and native integrations with Snowflake, BigQuery, Redshift, Salesforce, and Shopify.
Faraday is designed for data science and engineering teams at consumer-facing businesses including retail/e-commerce, home goods/services, financial services, insurance, and health/wellness. It serves marketing agencies, performance marketing firms, SaaS platforms, and agentic AI platforms that need grounded customer context. Teams use Faraday for lead prioritization, adaptive discounting, subject line personalization, sales rep assignment, loyalty targeting, lookalike audiences, personalized bundling, and market expansion.
The platform emphasizes responsible AI with SOC 2 Type II certification since 2020, HIPAA compliance (BAA available), GDPR and CCPA compliance, NIST 800-53 risk management, HackerOne penetration testing, and ethical data sourcing without third-party cookies or social scraping. Faraday is not a general-purpose AI platform or CDP—it specifically focuses on predicting individual customer behavior at scale.
Faraday pricing
Pricing model: Free
Signup is free. The website offers a 'Get started for free' option without displaying specific pricing tiers or plan details. Enterprise pricing and custom plans are available by meeting with an expert. The platform provides API access, no-code dashboard access, and multiple deployment options including real-time API, MCP server, and batch deployment into existing tech stacks.
Faraday pros
- 1,500+ consumer data points on 240 million U.S. adults
- Real-time API with responses under 200ms
- Built-in consumer data eliminates need for licensing or scraping
- Custom predictive models built automatically from first-party data
- No-code dashboard for point-and-click model building
- Native MCP server for AI agent integration
- Direct integrations with Snowflake, BigQuery, Redshift, Salesforce, Shopify
- Bias detection and mitigation built into platform
- Prediction explainability shows why scores exist
- SOC 2 Type II certified since 2020
- HIPAA compliant with BAA available
- GDPR and CCPA compliant with 14+ state privacy laws
- Deploy in days rather than months
- Does not use third-party cookies or social scraping
- Privacy-preserving logical data isolation per client
- 50+ downstream integrations available
- Batch and real-time inference support
- Probability calibration for accurate predictions
Faraday cons
- Only covers U.S. adults and households, no international data
- Not a general-purpose AI platform for non-customer use cases
- Not designed for FCRA-regulated decisions like credit or employment
- Requires customer data upload to build custom predictions
- Dashboard runs on API so both share same limitations
- May be overkill for very small businesses with limited data
- Custom model building requires some data science understanding
- Real-time API may have cost implications at high volume
- Primary focus on prediction rather than data pipeline management
Frequently asked questions about Faraday
What is Faraday?
Faraday is a customer context platform founded in 2012 and headquartered in Burlington, Vermont. It enables consumer brands, marketing agencies, and AI platforms to access a rich database of consumer data called the Faraday Identity Graph (FIG), which contains over 1,500 data points on approximately 240 million U.S. adults and their households. Faraday also creates custom data points by rapidly building predictive models that combine FIG data with customers' unique first-party data. All capabilities are available via API, MCP, or batch deployment into existing tech stacks.
How can you get started with Faraday?
Customers can start using Faraday in multiple ways: enriching lead or customer lists with identity data (phone, email, address); obtaining more information about individuals or households by adding consumer information including demographics, financial signals, lifestyle attributes, and behavioral indicators; identifying top segments and best customers using cluster analysis; identifying which leads are most likely to buy using the Propensity model builder; identifying which products or services a customer is most likely to buy using the Recommender model builder; and identifying which customers are most likely to churn using the Propensity model builder.
What is a customer context platform?
A customer context platform combines, cleans, and synthesizes 1,500+ third-party consumer data points—including demographic, property, financial, and lifestyle data—into clear, actionable signals. These signals are combined with first-party data to power bespoke machine learning models, delivered seamlessly into existing tech stacks. Most companies have first-party data but lack visibility into customers' wealth, life stage, intent, and other key factors. Faraday closes this gap by enriching customer records with missing context, enabling AI systems and human teams to reach and convert customers with greater precision.
What is the Faraday Identity Graph?
The Faraday Identity Graph (FIG) is a deterministic consumer data foundation covering approximately 240 million U.S. adults and their households. It acts as the core intelligence layer for the Faraday platform, containing over 1,500 curated attributes per individual. These attributes include deep, longitudinal data covering demographics, financial signals, property details, and lifestyle metrics. Faraday uses this dataset to provide real-world context necessary to build custom predictive models and ground agentic AI workflows.
Why do teams switch to Faraday?
Teams switch to Faraday for faster integration (replacing slow flat-file transfers with real-time APIs and MCP, deploying in days rather than months), optimized context budgets (Faraday curates 1,500+ consumer signals into actionable intelligence instead of raw data dumps), AI grounding (providing persistent context layer of real-world data preventing AI hallucinations), and predictive power (combining brand's first-party history with third-party context to model future behaviors like churn risk or propensity to buy rather than just looking at past interactions).
How does one access Faraday's data?
Faraday offers multiple flexible deployment methods: no-code dashboard at app.faraday.ai for uploading data, configuring predictions, and exploring results visually; REST API for batch deployments and real-time lookups returning enriched identity and predictive scores in under 200ms; native MCP server allowing AI agents to securely retrieve customer context directly within their context window; and native integrations with data warehouses (Snowflake, BigQuery, Redshift) and 50+ downstream integrations with platforms like Salesforce and Shopify.
What data does Faraday use to make predictions?
Faraday draws on two distinct data sources: the Faraday Identity Graph (FIG) with over 1,500 consumer attributes on approximately 240 million U.S. adults and households covering demographics, financial signals, lifestyle attributes, and longitudinal history; and client customer records including transactions, conversions, and engagement data collected directly through brand interactions. Faraday matches these sources using identity resolution and builds custom predictive models for each client's specific use case with the unified dataset, curating only relevant datapoints rather than delivering raw data dumps.
What industries does Faraday serve?
Faraday primarily serves consumer-facing industries where understanding individual customer behavior at scale drives measurable revenue. Core verticals include retail and e-commerce (jewelry, furniture, apparel, subscription boxes), home goods and home services (roofing, renovation, HVAC, flooring, windows, solar), financial services and insurance (credit unions, banks, debt consolidation, specialty insurance), and health and wellness (boutique fitness, nutritional supplements). Faraday also provides data and ML infrastructure for marketing agencies and SaaS/agentic AI platforms.
How does Faraday ensure data is compliant and ethical?
Faraday maintains SOC 2 Type II certification since 2020 and is fully compliant with HIPAA (BAA available), GDPR, CCPA, and 14+ additional U.S. state privacy laws. Security is ensured through strict isolation and encryption (client data logically isolated and encrypted at rest and in transit), ethical sourcing (no third-party cookies or social scraping, never positioned for FCRA-regulated decisions), and continuous auditing (NIST 800-53 risk management program, HackerOne penetration testing, Checkr employee background checks).
How is Faraday different from a CDP?
A Customer Data Platform (CDP) manages data pipelines and organizes internal first-party data to track how customers have already interacted with a brand. Faraday acts as the intelligence engine, enriching the CDP with real-world customer context like wealth, life stages, and predictive scores. Faraday does not replace the CDP—it provides the grounded context that makes CDP data actionable. They are complementary tools with distinct roles: CDPs track past interactions while Faraday predicts future behavior.