Faraday compliance workflow automation

Faraday is a predictive analytics platform that uses AI to help businesses understand and act on customer data.

AI & Automation Developer Tools & APIs Legal & Compliance

What you can automate with Faraday

Faraday is a predictive analytics platform that uses AI to help businesses understand and act on customer data. It builds propensity models, customer segments, and predictive scores from your existing data — answering questions like which leads are most likely to convert, which customers are at risk of churning, and where to find more people who look like your best buyers. All of this happens without requiring your team to have data science expertise. The platform connects to common data sources including CRMs, marketing platforms, and transactional databases. Once connected, Faraday enriches your records with demographic and behavioural data, then applies machine learning models to surface actionable predictions. The results feed back into your marketing and sales tools, so your team can act on insights directly rather than staring at dashboards. For Australian businesses sitting on customer data but unsure how to extract value from it, Faraday offers a practical entry point into predictive AI. Pairing it with a solid automated data processing setup ensures clean data flows into the platform, while working with an AI agency can help you design the right models for your specific business questions. If you already use workflow automation tools, system integrations can push Faraday’s predictions into the platforms where your team actually works. Faraday is a strong choice for consumer-facing businesses, subscription services, and retail companies that want to move beyond basic analytics toward genuine prediction. If you have customer data and want to know what to do with it, this platform gives you a clear starting point.

Faraday FAQs

Frequently Asked Questions

Common questions about how Faraday consultants can help with integration and implementation

Faraday builds models for lead conversion likelihood, customer churn risk, lifetime value prediction, and lookalike audience identification. It can also score and segment customers based on their predicted behaviour.

No. Faraday is designed for business users and marketers. The platform handles the machine learning model building and data enrichment automatically. You configure what you want to predict, and Faraday does the technical work.

Faraday integrates with CRMs like Salesforce and HubSpot, marketing platforms, data warehouses, and transactional databases. It also enriches your first-party data with third-party demographic and behavioural information.

Faraday uses privacy-safe data enrichment practices and complies with major data protection frameworks. Review their privacy documentation to confirm alignment with your specific obligations, particularly under Australian privacy law.

Yes. Faraday is built to feed predictions and scores back into your CRM, email marketing platform, advertising tools, and other systems. This means your team acts on insights within the tools they already use daily.

Faraday works best when you have at least a few thousand customer records with outcome data — for example, who converted and who did not. The more historical data available, the more accurate the predictions tend to be.

How it works

Implementing Faraday

Step 1

Connect Your Data Sources

Link Faraday to your CRM, marketing platform, or data warehouse. The platform supports a range of common integrations and can also ingest CSV files for initial setup.

Step 2

Define Your Prediction Goals

Tell Faraday what you want to predict — lead conversion, churn risk, purchase likelihood, or another outcome. The platform uses this to determine which models to build and which data points matter most.

Step 3

Let Faraday Enrich and Model Your Data

Faraday enriches your existing records with additional demographic and behavioural data, then trains machine learning models against your defined outcomes. This process runs automatically.

Step 4

Review Predictions and Segments

Examine the predictive scores, customer segments, and insights that Faraday generates. Check that the models align with your business intuition and adjust configuration if needed.

Step 5

Push Predictions Into Your Workflow Tools

Route Faraday's scores and segments back into your CRM, email platform, or advertising tools. This allows your sales and marketing teams to act on predictions without switching between systems.

Step 6

Monitor and Retrain Models Over Time

As new customer data accumulates, review model accuracy and retrain as needed. Faraday provides performance metrics so you can see whether predictions remain reliable over time.