Pecan AI

Pecan AI is a predictive analytics platform built around a Predictive AI Agent that lets business and analytics teams turn historical, event-level data into production predictions without building a conventional machine-learning pipeline. Current use cases include churn, customer lifetime value, lead conversion, demand and inventory forecasting, revenue, campaign ROAS, upsell, win-back, and fraud risk.

1. Predictive workflow: users start with a business question, such as which customers are likely to churn or how much demand to expect. Pecan’s agent handles data preparation and feature engineering, while its automated modeling pipeline trains and evaluates candidate models, validates them against held-out data, and selects a model according to the chosen optimization metric. Predictions can then run once or on a recurring schedule.
2. Business use cases: marketing teams can predict conversions, LTV, campaign performance, and customer response; sales teams can score leads and accounts; customer-success teams can identify churn risk; operations teams can forecast demand and inventory; and finance teams can model outcomes such as revenue and cash flow. This makes Pecan focused on tabular business prediction rather than general-purpose generative AI.
3. Data connections and activation: Pecan connects directly with platforms including Snowflake, Google BigQuery, Amazon Redshift, Microsoft SQL Server, PostgreSQL, MySQL, Oracle, Salesforce, HubSpot, Databricks, ClickHouse, and S3-hosted files. Connection capabilities differ: systems such as Snowflake, BigQuery, Redshift, and Salesforce support both reading data and writing predictions, while HubSpot is currently documented as an inbound/read connection. Predictions can also be scheduled back to supported warehouses, databases, CRMs, or other destinations.
4. Commercial model: current plans are Starter, Team, and Business. Starter includes two prediction batches per month and storage for up to 500 million rows; Team increases this to 10 batches and 2 billion rows; Business provides custom prediction volume and up to 5 billion rows. Pecan does not publish fixed dollar prices and directs buyers to sales for a quote. Subscriptions are currently offered on an annual billing cycle, with larger deployments able to add capabilities such as advanced monitoring, custom dashboards, granular explainability, and specialized deployment requirements.

Pecan AI is most relevant to organizations with historical business data and recurring predictive decisions that want models built, validated, refreshed, and delivered into operational systems without maintaining a full internal data-science workflow.