Data science for
Data scientists analysts.

Using Pecan, most data analysts successfully build their first model in just days. Compare that to the months a traditional data science team would need to hand-build custom predictive models. Our automated data prep capabilities, SQL-based modeling, and generative AI copilot help analysts speed through the process. Your business can benefit from accurate predictive modeling faster with Pecan than with any other predictive solution.

You can choose one of our packages or let us customize a quote for your needs. Other tools may have unclear pricing based on your compute or usage, but with Pecan, you’ll know in advance what your costs will be, making planning and budgeting much more straightforward.

You choose which data gets imported to Pecan’s cloud environment for model training. Anything you don’t select stays put in your data center. No PII is ever required for training models. Plus, we take exceptional measures to ensure the safety of your data. We’re happy to discuss any specific concerns you have, so don’t hesitate to contact us with questions.

One word: Easily. We’ve got pre-built integrations to many of the most widely used data and business tools so that you can connect in just a few clicks. And if you need a connection that’s not on the list right now, let us know. It could already be in the works!

Generally, Pecan needs at least 6 months of event-based data with over a thousand daily events (e.g., purchases, registrations, active users, etc.). To make predictions further into the future, it helps to have more data from the past. For example, if you want to predict what will happen a year from now, we recommend at least 16 months of historical data.

Pecan’s automated processes detect and fix common issues in data quality—such as missing data, outliers, or duplicated data. These proprietary, unique methods eliminate the tedious, time-consuming work required to create an AI-ready dataset. This preparation also improves predictive models’ performance and helps you get the most value from your data.