Turn scattered documents into answers your team can trust.

Most teams have files everywhere and answers nowhere: PDFs in Drive, policies in docs, support knowledge buried in threads, and too much context trapped in people's heads. Ragbee turns that mess into one private, grounded knowledge layer for documents, chat, support, voice, and bots.

Upload files. Ingest URLs. Connect cloud folders. Search semantically. Ask grounded questions. Power Zoom, Telegram, Discord, support email, shipping workflows, voice agents, and internal support tools from the same source of truth.

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Built for private workspaces, not public toy demos.
Ragbee is designed for tenant-aware teams, private storage, and grounded answers tied to real source material. Start free — no credit card required.

Product point of view

"Ragbee is not just a place to upload files. It is a private knowledge product you can operate across chat, support, voice, and automation."

Not another file dump Documents are searchable, grounded, scoped, and reusable across delivery channels.

Not a hallucination engine Answers are meant to be rooted in the current workspace, not free-floating guesses.

Built for operations Support inboxes, voice calls, connectors, and reporting live alongside retrieval and chat.

One source of truth The same workspace can power humans, bots, and phone agents without duplicating knowledge.

Simple pricing

Start free, upgrade when you're ready. No credit card required to try it out.

Free

$0/mo

1 workspace
25 documents
100 queries/month
1 connector
No chatbots
No API access

Get started

Why Ragbee exists

AI around documents usually breaks in one of two ways: either it stays trapped as a demo chat widget bolted onto uploads, or it gets spread across too many disconnected tools to trust. Ragbee takes a different approach. The idea is simple: build one private system where documents can be ingested, organized, retrieved, synced, questioned, and delivered into the channels where people actually work.

A private knowledge layer Put uploads, URLs, synced folders, and extracted knowledge into one tenant-aware system instead of scattering them across separate tools.

Grounded answers, not loose summaries Retrieval is scoped to the current workspace so the system stays useful for actual policy, support, and operations questions.

One backend, multiple delivery channels Use the same knowledge base for dashboard chat, support workflows, Zoom Chat, Telegram, Discord, and voice.

What you can do with it

Ingest and organize documents

Upload files and ingest URLs
Handle duplicates and versions
Use soft delete and trash instead of destructive workflows
Keep assets private with MinIO-backed storage

Search and chat with grounded context

Semantic retrieval with pgvector
Workspace-scoped question answering
Extracted facts and hybrid retrieval
Separate Proxi-Web mode for web-aware conversations

Connect external sources

Google Drive browse, import, and folder connectors
Dropbox import and folder connection support
Recursive sync and scheduled sync
SharePoint direction already scaffolded
Tenant-wide support integrations like shipping manager and support email

Run support workflows from the same workspace

Tenant-scoped support inbox across SMS, voice, and email
Shipping-aware replies for package lookup workflows
Voice call visibility and transcript capture
Cross-channel reporting and export
AgentMail-backed inbound and outbound support email

Power bots and assistants

Tenant-owned chatbot definitions
Zoom Chat, Telegram, and Discord support
Conversation history for more natural follow-ups
Separate runner architecture for channel execution

Operate it like a product

Invite-only signup and tenant roles
Workspace separation and API keys
Admin visibility with Django
Native reporting instead of opaque black boxes

Use cases that fit naturally

Employee handbook assistant Answer PTO, leave, benefits, and policy questions without forcing people to dig through folders or PDFs.

Customer support knowledge base Give support teams a grounded answer layer they can use in inboxes, chat, phone workflows, and shipping-related support requests.

Internal operations search Turn SOPs, training docs, playbooks, and internal notes into a searchable operating system for the team.

Voice-enabled document support Reuse the same workspace for phone answers, transcript logging, and follow-up review.

Bot-backed workspace help Bring the knowledge base into the channels people already use: Zoom, Telegram, and Discord.

Private RAG infrastructure Use Ragbee as a tenant-aware backend for apps, automations, and internal tools that need grounded document context.

Underlying technology and tools

The product story comes first, but the underlying stack matters because reliability, privacy, and delivery discipline matter. Ragbee is intentionally built on boring, inspectable infrastructure where possible, with AI components used where they actually add value.

Core application layer Django drives the main product: auth, admin, dashboard, tenant/workspace control, connectors, reports, support views, and APIs.

Database and retrieval Postgres is the system of record, with pgvector for semantic search and retrieval across workspace documents.

Embeddings and generation OpenAI embeddings power semantic indexing, while Groq-hosted generation is used for cost-efficient chat and rewrite tasks.

Private storage Files and generated assets are kept in private MinIO-backed object storage rather than open public blob URLs.

Execution plane separation Chatbots and voice agents live in separate services so Django stays the control plane and channel execution stays modular.

Operational tooling Celery handles background work, scheduled connector syncs, and ingestion workflows, while systemd-backed services keep the app, workers, bots, and voice agents running cleanly.

Get started

Start free — no credit card required. Upload a few documents, connect Google Drive, and start asking real questions against a live workspace. Upgrade to Pro or Business when you need more.

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