Orama

Design, train, and deploy custom enterprise machine learning models directly on your private data

Pricing model

Free Tier

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Metis to evaluate your data readiness and run custom machine learning models on private infrastructure. It measures how ready your internal databases and records are to support specific business decisions before building models. The software connects to existing data warehouses, prepares datasets, and trains models tailored to your operational goals. It then deploys these models into production to serve automated decisions, search indices, and agents while monitoring actual business outcomes and tracking financial return on investment over time.

What Orama does

Assess data readiness for automated decisionsConnect internal data lakes to machine learning pipelinesTrain custom machine learning models on private dataDeploy search indexes and predictive models on enterprise infrastructureRetrain operational models when source records changeTrack return on investment for deployed production modelsRun automated decision systems without external data leakageScores data readiness for specific decisions on a scale from zero to tenConnects directly to existing data warehouses, application databases, and sensorsTrains custom machine learning models directly on proprietary enterprise datasetsRuns inside your private cloud, on-premises servers, or dedicated hardwareProvides forward-deployed engineering support to assist internal technical teamsTracks model performance against business metrics and financial return on investmentIntegrates with the open-source OramaJS index for search and retrieval workloads