DevIO
AI-powered developer tool that provides a secure mobile interface for locally hosted LLMs (Ollama), with a focus on data privacy and offline functionality.
DevIO turns a phone into a secure control interface for local LLM servers. It is designed for developers who want fast AI workflows without sending sensitive data to third-party cloud services.
Role
Product Engineer
Timeline
Ongoing
Delivery
Structured implementation across design, engineering, and release phases.
Challenge
- Build a clean mobile UX for complex LLM interactions.
- Keep model communication secure across local networks.
- Support practical offline and low-connectivity workflows.
Solution
- Implemented a Flutter app with a modular architecture and predictable state management.
- Designed a local-first connection flow to servers like Ollama.
- Optimized interactions for quick prompts, history, and session continuity.
Architecture
- Flutter client with feature-based modules.
- Local LLM backend compatibility (Ollama-first design).
- Reusable service layer for model requests and response parsing.
Outcomes
- Shipped to the App Store with production-level UX.
- Enabled practical AI usage with stronger privacy guarantees.
- Established a base for additional AI workflows in mobile.
Next Steps
- Expand multi-model routing options.
- Add richer context management for longer sessions.
- Introduce advanced developer tooling around prompt templates.
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