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Live beta
AI data management terminal

Featured AI Product

Atlas Beta / AI Data Management Terminal

Atlas is built around one honest promise: connect the tools you already use, search across them through one interface, and stay explicit about connector coverage, permissions, and beta limitations.

Project role

Product, platform, and full-stack engineering

Live links

Workflow overview

How the product is structured

Contact
1

Workspace

Connected search layer

Atlas treats search, preview, and browsing as the primary interface across approved providers.

2

Connectors

Source-aware capability model

Each connector advertises what is actually live, what actions are supported, and what limits still exist.

3

Runtime

Deliberate beta to scale path

The current runtime stays lean while the architecture is already framed for OpenSearch, Redis/BullMQ, and object storage.

Focus areas

connected search
data management
connector architecture
permission-aware actions
full-stack TypeScript
search infrastructure
background jobs
beta product systems

What the product is solving

Most teams already have the data they need, but it lives across too many systems. Atlas brings that sprawl into one terminal-like workspace for connected search, previews, and source-aware actions without pretending every connector works the same way.

A connected workspace terminal for searching, previewing, and managing approved data across files, docs, chat, code, design, and project tools from one place.

What is already working

Invite-based beta onboarding, a public updates hub, and FAQ/status surfaces that clearly separate live functionality from roadmap items.
Live connector coverage across Google Drive, Gmail, Google Photos, OneDrive, Dropbox, GitHub, Notion, Slack, Box, GitLab, Confluence, Microsoft Teams, Figma, Linear, Airtable, and AWS S3.
Connected search, previews, browsing, and selected file actions driven by source-aware permissions and connector-specific capabilities.
Lean beta runtime with Postgres search today plus a clearer production path toward OpenSearch, Redis/BullMQ, and object-storage-backed scale.

AI + platform stack

AI stack

Connected retrieval
Search ranking
Preview extraction
Permission-aware actions
Automation hooks

Platform stack

Next.js 14
React 18
TypeScript
Prisma
PostgreSQL
BullMQ
Redis
Supabase
S3-style artifact storage
OpenSearch
NextAuth
Cloudflare
Railway
AWS-target architecture

What I focused on

Atlas already exposes 16 live connectors and keeps roadmap connectors separate instead of blurring what works now versus later.
The product is explicit about source-aware actions such as browse, search, preview, download, upload, and folder creation only where a connector truly supports them.
The beta surface is honest about manual onboarding, public updates, and current limitations, which makes the product feel authored instead of overpromised.