Graphite Note

What is Graphite Note?

Graphite Note is a no-code predictive analytics platform for business analysts and small and midsize teams. It builds models for churn, lead scoring and demand forecasting from tabular data and adds decision impact analysis and prescriptive recommendations. The company is based in Zagreb, Croatia.

Key capabilities of Graphite Note

• No-code model building: create predictive models from tabular data without writing code
• Churn and lead scoring: ready-made templates for customer retention and sales prioritization
• Demand forecasting: time series forecasts for planning and inventory decisions
• Causal modeling: answers what-if questions about the impact of a decision, not only what will happen
• Explainable predictions: shows which factors drive each prediction
• Prescriptive playbooks: turns predictions into recommended actions that can be activated in other tools

How Graphite Note works

Users connect or upload tabular data from sources such as Snowflake, BigQuery, Databricks, Salesforce or HubSpot, pick a predictive template, and Graphite Note trains and evaluates a model automatically. Results come with explanations of the driving factors and, on higher tiers, causal impact analysis and playbooks. Analysts review model outputs before acting on them.

Who uses Graphite Note?

Business analysts, marketing, sales and operations teams at small and midsize companies use Graphite Note when they need predictions without a data science team. Enterprise buyers get onboarding and managed services.

Graphite Note pricing

A free Sandbox tier offers predictive templates only, without causal modeling, production data or multi-user workspaces. Third-party sources report paid plans of roughly $100 to $499 per month and an Enterprise plan from $50,000 per year, but the vendor pricing page could not be fetched, so confirm current rates.

Graphite Note alternatives

Graphite Note is compared with Obviously AI, Qlik AutoML, Kumo, Nixtla and Unit8. Obviously AI is also no-code; Nixtla focuses on time series forecasting libraries and Kumo on relational data models.