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.
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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.
- CategoryMachine Learning Platforms
- Pricing ModelFreemium
- DeploymentOn-Device
- PlatformsiOS, Android, Desktop
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?
Upload: Upload your dataset
Fine-tune: Use the visual interface to fine-tune models
Export: Export models as GGUF for local deployment
Deploy: Deploy models on-device or locally
Ertas AI's Use Cases
- Healthcare AI
- SaaS Product Teams
- Customer Support
- Legal AI
- Finance AI
