Your business history already knows what’s coming next

Upload a CSV of your customer history with a column marking who left, pick that column as the outcome, and EasyDeploy AI trains the model. It searches thousands of candidate pipelines and returns one with a performance report, so you can see what it gets right before you rely on it. The run takes minutes and involves no code.

Less than people expect. Models do best with a few thousand rows, and a few hundred customers with the outcome recorded is enough to start: GreenifyAI trained on 928 labeled listings and scored 19,484. What matters more than the count is that both outcomes appear often enough to learn from, and the model report tells you whether your rows were enough before you rely on it. Each row records what you knew about a customer on an as-of date and whether they churned within your prediction window, for example 90 days. Our data readiness guide covers what the rows need to look like.

It depends on who will run it. A team with a customer export and no data scientist wants a self-serve platform that trains on that export; a team with a warehouse and budget for a partner wants a serviced one; a customer success team that needs a workflow more than a model may be fine with the score inside its CRM. We compared ten tools on how fast a non-technical team gets to a working, explainable model.

A ranked list. Upload a CSV of the customers, leads or invoices you want scored, and you get the same rows back with a prediction for each, ready to download, sort and hand to whoever acts on it. You can also score one record at a time in the app, or have a system or Claude request predictions through the REST API and the Claude connector. Paid plans add a live endpoint that keeps a model always on for real-time scoring.

Every model is scored on records it never saw during training, and the report shows the results in plain numbers, along with which fields drove them, before you rely on it. If the first model is not good enough you find out from the report, not from your customers, and you can fix the data and train again. In our churn example the first model missed 48% of real churners. Rebalancing the training data and running the search again cut that to 17% on the same untouched holdout.

It stays yours. Your data is encrypted in transit and at rest, it is used to train your models and nothing else, and it is never sold. We improve the service using anonymized, aggregated usage data, never your datasets, your predictions or your models. You can have your account and everything in it deleted on request.

Yes. Export your leads with a column showing which ones closed, upload the CSV, and EasyDeploy AI trains a model that scores new leads by how closely they resemble the ones that won. Predictions come back as a ranked list your sales team can work from the top, in batch or one record at a time.

Connect QuickBooks or Shopify to your AI assistant, or export your order history as a CSV, and train a model on it. EasyDeploy AI reads a CSV from QuickBooks, NetSuite, Shopify or any system that can export one, so there is no integration to build first. A year of sales by product and week is the minimum and two years is better, so the model sees every season twice.

Yes. EasyDeploy AI has an open-source MCP connector, so an assistant can upload a dataset, train a model, read its report and run predictions as tools inside a conversation. It works in Claude, Claude Code, Cursor, VS Code and any other MCP client. The assistant does the reasoning and EasyDeploy does the predicting.