holaOS: a local-first working agent that builds durable professional memory via 100+ workplace integrations

What it solves

HolaOS addresses the problem of AI agents lacking persistent, deep context about a user's specific work environment. It eliminates the need to manually copy-paste data or re-explain background by automatically integrating with workplace tools and maintaining a local, durable memory of the user's working state.

How it works

HolaOS operates as a local-first desktop application that connects to over 100 workplace integrations (such as GitHub, Slack, and Jira) via OAuth. It uses a "Memory Management system" to fetch and compress data from these tools, storing it locally as Markdown files embedded with SQLite vec. This allows the agent to use Retrieval-Augmented Generation (RAG) to recall specific facts and context. To maintain efficiency in long conversations, it employs "Safe Session Compaction," which compresses older history into structured checkpoints while reserving most of the model's context window for active reasoning.

Who it’s for

It is designed for professionals and developers who want a "working agent" that understands their business context, manages tasks across multiple apps, and keeps sensitive working memory stored locally on their own machine.

Highlights

• Local-First Memory: Stores working context as local Markdown and SQLite embeddings, ensuring the user owns and controls their data.
• Deep Integrations: One-click OAuth connectivity to 100+ tools including Linear, HubSpot, and Gmail.
• Session Compaction: Prevents token bloat in long-running sessions by folding old history into goals and decisions.
• Integrated Workspace: A production-grade desktop UI that combines agent chat, file inspection, and a customizable dashboard, removing the need for a CLI.
• Browser Integration: Ability to integrate browser profiles to handle web-based work beyond standard APIs.