Plug-and-Play Bulk Scoring Server

An out-of-the-box batch scoring and decision inference service for teams without ML infra

Problem

Developers regularly need to score or rule-check tens of thousands of records at once (fraud rules, lead scoring, content grading), but standing up inference means model loading, batching, concurrency and GPU memory management. One builder shipped a small inference server just to fill this gap, and new projects still lack lightweight reference backends.

Solution

A single-binary or Docker batch inference daemon: reads CSV/JSON or a database table, runs models or rules per task config, and writes results back, with batching, retries, progress and validation built in. Aimed at small-to-medium data volumes, no training needed.

Users

SaaS teams needing batch scoring, data engineers, and solo backend developers

MVP

Single-container deploy; CSV/JSON in and out; model loading plus batch scheduling; progress and failure retries; one sample scoring scenario

Revenue

Open-source core plus hosted version billed per records processed, or an enterprise license with deployment support

Why now

AI is moving to production where batch scoring beats chatbots yet lightweight tooling is scarce; a solo dev can ship a working MVP in weeks