Sero is a private local AI workspace designed for offline document retrieval and research. It empowers users to search, summarize, and understand documents like PDFs, notes, code, and local files entirely on their Mac, ensuring data privacy and security.

• Local First: Search and chat with documents even without an internet connection. Your files never leave your Mac, with 0% telemetry collection.

• Bring Your Own AI Models: Utilize lightweight local models through Ollama, giving you full control over performance and privacy. Compatible models include Qwen 3.5, Llama, Mistral, and DeepSeek.

• Expertise in Private Knowledge Retrieval: Find insights across various document types including PDFs, Markdown files, technical documentation, and research materials with AI models tailored for real-world workflows.

• Deep Document Understanding: Surface key insights, generate summaries, and identify important sections from lengthy reports, proposals, and technical documents instantly.

• Developer Knowledge Retrieval: A fast, local workspace built for technical teams to search architecture documents, API keys, code snippets, OCR scans, and structured files.

• Privacy Architecture: Sero indexes, embeds, and reasons over your files locally with offline AI processing. No cloud uploads, no telemetry, and no remote file access.

• Open Source: Sero is fully open source, allowing for transparency, local execution, workflow customization, and the use of your own models without vendor lock-in.

• Compatibility: Optimized for Apple Silicon, Sero works well on MacBook Air, MacBook Pro, Mac Mini, and Studio devices, including base M1 and M2 systems.