Resources
Built to be Transparent. Built to be Trusted.
Explore how Clarecast operates, what makes our forecasts the best in class, and where we're going next.
Built to protect. Designed for trust.
At Clarecast, security and privacy are foundational to how we build and operate our predictive intelligence services. We maintain a layered approach to protecting data through identity and access management practices, encryption, cloud-native infrastructure safeguards, and thoughtful oversight of third-party service providers.
Our services are built on leading cloud and data infrastructure providers, and we maintain operational and security practices designed to support the confidentiality, integrity, and responsible handling of data. As Clarecast continues to grow, we remain committed to evolving our security and privacy program in alignment with industry best practices and customer expectations.
Built on Databricks. Validated by Databricks.
Clarecast is a Databricks Built On Startup, with our entire predictive forecasting engine running natively on the Databricks Data Intelligence Platform. This isn't a connector or a downstream integration. The architecture, the model training, the production inference, and the customer data delivery all happen on Databricks.
For customers already on Databricks, that means Clarecast intelligence can be delivered directly into your environment through Delta Sharing — with no data movement and no separate pipeline to maintain. For everyone else, it means our forecasts are built on infrastructure designed for AI workloads at scale.
We compared our engine to 18 foundation models.
Why would a customer of ours not just prompt a general LLM to get forward-looking insights on where a business was headed? We needed to answer how we stack up and how predictions change month over month.
So Clarecast built a benchmark study comparing our forecasting engine against 18 foundation models across 2,122 public companies. The report covers our methodology, accuracy metrics, the specific signals that drive our predictions, and how our results stack up against general-purpose AI alternatives.
If you're evaluating predictive intelligence vendors, or considering whether to build something internally, this report is the most rigorous head-to-head comparison available.