Project Info

Doryo

Devpost

🧠

Inspiration

In today’s remote and hybrid world, collaboration often feels fragmented β€” scattered across chat tools, notes, and task managers. We wanted to reimagine what it means to β€œwork together” when one of your teammates is an intelligent agent. Doriyo (ドγƒͺヨ, Japanese for coworker) was born from a simple question: β€œWhat if your conversations could think, remember, and act with you?” We envisioned a shared workspace where people can chat naturally, brainstorm ideas, and have an AI coworker that listens, remembers, and takes action when needed. Whether it’s creating a GitHub repo, generating a Notion itinerary, or summarizing a discussion, Doriyo acts as a quiet, capable teammate. πŸ€–

What it does

Doriyo is a real-time conversational workspace that brings humans and AI together. πŸ—£οΈ Collaborative chat: Create or join workspaces and collaborate in real time. πŸ§‘β€πŸ’» AI coworker (@Doriyo): Mention @ask to query context or @act to perform an action. πŸͺ„ Integrated actions with Composio: Connect tools like GitHub, Notion, and Google Drive. Example: β€œ@act create a Next.js template repo for our project.” β†’ Doriyo commits the scaffold to your GitHub. Example: β€œ@act create a Next.js template repo for our project.” β†’ Doriyo commits the scaffold to your GitHub. 🧠 Memory: Doriyo remembers previous discussions to provide contextually aware responses. Think of it as Slack + Notion + an AI coworker combined into a single workspace. 🧩

How we built it

Frontend: React + Vite for a fast, modular interface. Firebase Firestore for real-time message synchronization and presence tracking. Firebase Auth for secure login, signup, and workspace invites. Backend: FastAPI (Python) for handling requests, orchestrating actions, and managing session logic. Letta to define and manage each user’s personal AI agent, maintaining context and persistence. Composio for secure integration with third-party tools like GitHub, Notion, and Google Drive. Claude for language understanding, reasoning, and conversational context generation. The result is a seamless full-stack system where multiple users can chat, mention the agent, and see actions happen live β€” all backed by real-time data sync. 🧱

Challenges we ran into

Maintaining real-time consistency for multi-user chat sessions using Firestore transactions. Designing a safe and permissioned workflow for actions so only workspace hosts can approve executions. Handling long-term memory and summarization efficiently without overloading the context window. Creating a cohesive UX where the agent feels like part of the team, not just another bot. πŸ†

Accomplishments we're proud of

Built a functional, multi-user AI workspace with persistent context and real-time collaboration. Integrated Letta and Composio to allow the AI to act directly on connected user tools. Achieved smooth, low-latency updates using Firebase Firestore listeners. Designed a clean, modern interface that makes AI feel like a true collaborator. πŸ’‘

What we learned

Building multi-user, multi-agent systems is as much a design problem as a technical one. Clear permission boundaries and confirmations improve user trust and safety. Contextual memory dramatically improves AI usefulness in collaborative settings. Real-time Firestore updates simplify sync logic compared to maintaining custom WebSocket servers. πŸš€

What's next

for Doriyo 🎧 Voice support: Integrate SFU (LiveKit) for voice-based interaction. 🧩 Multi-agent collaboration: Let personal agents cooperate on shared goals. πŸ“„ Automatic summaries: Generate meeting notes and documents from conversations. 🏒 Enterprise support: Role-based access control and organization-level workspaces. 🌐 Public sharing: Export or share interactive workspace transcripts. 🧭 In short Doriyo is your AI coworker β€” listening, thinking, and acting with your team in real time. Collaboration shouldn't just be about talking; it should be about doing, together.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • FirebaseIn code
  • HTMLIn code
  • JavaScriptIn code
  • ReactIn code
  • FastAPIClaimed
  • PythonClaimed

5 of 7 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

92 KB

Source files

16

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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