OrchestraML Agentic ML Pipeline Platform
An agentic ML pipeline platform built for tech students and developers who understand ML concepts but don't want to write boilerplate sklearn pipelines.
Project Case Study
OrchestraML is an agentic ML pipeline platform built for tech students and developers who understand ML concepts but don't want to write boilerplate sklearn pipelines.
HOW IT WORKS
Describe your ML goal in plain English → 8 specialized agents handle everything → you approve every critical decision → get a deployed model.
THE 8 AGENTS
HUMAN-IN-THE-LOOP
6 hard checkpoint gates where the pipeline PAUSES and waits for your approval. You're always in control. Nothing runs without your sign-off.
WHAT YOU GET
SECURITY
AES-256 encrypted dataset storage. Datasets auto-deleted after pipeline. Only your trained model is kept.
FREE PLAN: 2 pipelines/day, datasets up to 50k rows, all features included.
Key Engineering Milestones
8-Agent Orchestration Engine
Orchestrated 8 specialized agents (Orchestrator, Dataset, EDA, Cleaning, Feature, Modeling, Evaluation, Deployment) using Gemini Flash, pandas, FLAML AutoML, SHAP, and BentoML to automate the complete ML lifecycle.
6-Gate Human-in-the-Loop Safeguards
Implemented 6 hard checkpoint gates where the pipeline automatically pauses and waits for user approval, ensuring developers remain in control of all data cleaning, modeling, and evaluation decisions.
Comprehensive Outputs & REST API
Generates full reports with metrics, SHAP explainability plots, confusion matrices, audit logs, and downloadable packages (model.pkl + prediction scripts) or one-click BentoML REST API deployments.
Secure & Scalable Architecture
Built using FastAPI, Next.js 15, and Supabase, featuring AES-256 encrypted dataset storage and automatic dataset deletion post-pipeline run to guarantee privacy.