Radal

Radal is a no-code platform to fine-tune small language models using your own data. It allows users to connect datasets, configure training visually, and deploy models in minutes. The platform is built for startups, researchers, and enterprises needing custom AI without MLOps complexity.

How to Use

Radal simplifies the process of training small language models through a visual, no-code interface. Users can connect datasets, drag and drop elements to configure training flows, and interact with an AI Copilot. Models can be trained with one click, iterated visually, and deployed quickly, even on edge devices.

Key Features

• No-code visual training flow
• AI Copilot for tailored flow construction
• Hugging Face integration for auto-push
• Export quantized models for local/edge deployment
• One-click training and visual iteration

Use Cases

• Industrial IoT: Predictive Maintenance (fine-tune edge models on sensor logs for real-time anomaly detection and reduced downtime)
• Healthcare: On-Prem Privacy (fine-tune clinical models on patient data for secure note drafting within hospital networks, meeting HIPAA requirements)
• LegalTech: Legal Teams (fine-tune legal models on firm’s data to draft motions, surface key precedents, and save attorney time)
• EdTech: Offline Mobile (train on-device SLMs with curriculum content for instant homework help without internet connectivity)
• SaaS: Customer Support (fine-tune models on support tickets and FAQ docs to create AI agents for routine questions)
• FinTech: Edge Payments (fine-tune edge models on transaction logs for real-time fraud detection on card terminals)