Ertas AI

Description

Ertas AI is a platform designed to help users build custom AI models for deployment on devices such as iOS, Android, or desktop applications. The platform emphasizes privacy, allowing models to run offline with zero per-inference cost. Users can upload datasets and fine-tune models using a visual interface without needing any coding skills. The training is conducted on cloud GPUs, and the models can be exported as GGUF for local inference. Ertas AI supports popular open models like Gemma, Qwen, Llama, Mistral, and Phi, focusing on models that can be deployed locally or on-device.

The platform offers various pricing plans, starting with a free tier that provides 30 credits per month, suitable for smaller models. Paid plans offer more credits, larger model support, and additional storage. The highest tier includes features like priority GPU queue and white-label API access. Ertas AI is designed for indie developers, startups, agencies, and solo builders who want to integrate AI into their products without the complexity of managing infrastructure.

Ertas AI also provides solutions for various industries, including healthcare, SaaS, customer support, legal, finance, and education. The platform ensures compliance with regulations like GDPR, HIPAA, and the EU AI Act, offering features like encrypted storage and audit trails. Users can manage their models through the Model Studio and Hub, with managed API deployment on the roadmap.

Integrations with popular AI tools and platforms such as Hugging Face, llama.cpp, and Ollama are supported, allowing users to connect Ertas AI with their existing workflows. The platform is built for app builders who want to ship AI-powered products efficiently and cost-effectively.

Ertas AI's Core Features

• Visual fine-tuning interface

• Cloud GPU training

• GGUF export for local inference

• Parallel runs and live training metrics

• Dataset synthesis with AI-assisted generation

• Per-client LoRA adapters

• Compatible with Ollama, llama.cpp, LM Studio

• Privacy-first platform

How to use Ertas AI?

1. 1

   Upload: Upload your dataset

2. 2

   Fine-tune: Use the visual interface to fine-tune models

3. 3

   Export: Export models as GGUF for local deployment

4. 4

   Deploy: Deploy models on-device or locally

Ertas AI's Use Cases

• Healthcare AI
• SaaS Product Teams
• Customer Support
• Legal AI
• Finance AI

FAQ from Ertas AI

• Do I need ML experience to use Ertas AI?

  No, Ertas AI handles the training workflow, GPU setup, model packaging, and export path.

• Is Ertas AI only for on-device AI?

  No, it supports both on-device and server-side inference, managed GPU deployment, and more.

• What do I get after training a model?

  You receive a fine-tuned model artifact that can be tested, exported, and integrated into your app.

• What models can I train with Ertas AI?

  Ertas supports models like Gemma, Qwen, Llama, Mistral, and Phi.

• Does Ertas AI store my training data?

  Yes, Ertas stores datasets for rerunning experiments and comparing training runs.

• What parts of Ertas AI are available today?

  Model Studio is available for data upload, model training, testing, and export.

• Can I try Ertas AI for free?

  Yes, the free plan offers 30 credits per month without requiring a credit card.

• How does Ertas AI pricing work?

  Pricing is based on monthly plans, with credits covering fine-tuning runs and other features.