What Is Raven for ERPNext? Team Chat, AI Agents & Setup (2026)

Raven started as a straightforward answer to a common gap: ERPNext teams needed internal chat, and buying a separate Slack subscription meant paying for and maintaining yet another tool alongside the ERP itself. Raven closes that gap natively — channels, direct messages, document alerts tied to ERPNext records — all inside the same Frappe-based system.

What makes Raven worth a dedicated look now is v2's AI agent layer, which turns it from "internal Slack alternative" into something that can actively act on your ERPNext data through conversation. I am Manoj, an ERPNext and Frappe implementation consultant at MithTech, and this is what Raven actually does today.

What does Raven actually do inside ERPNext?

Raven provides team chat — channels, direct messages, and document-linked alerts — running natively inside an ERPNext instance, plus, since v2, no-code AI agents that can read instructions in a chat message and act on ERPNext data in response. The chat layer alone replaces a standalone Slack or Teams subscription for internal communication; the AI agent layer is the part that's newer and less widely understood.

Document alerts are a specific, practical feature worth calling out: instead of a generic notification system, Raven can post to a channel when a specific ERPNext document changes — a Sales Order is submitted, a Purchase Invoice is approved — keeping the team's conversation tied to what's actually happening in the ERP, not a separate activity feed nobody checks.

Skimmable summary: Raven is native team chat for ERPNext (channels, DMs, document-linked alerts) plus, since v2, no-code AI agents that can act on ERPNext data from a conversation — two genuinely separate capabilities in one app.

How do Raven's AI agents work?

Raven's AI agents work by connecting to OpenAI's Assistants API behind a no-code configuration layer — you define an agent with specific instructions and a defined task, and the agent can then create or update ERPNext records, or read a receipt or invoice image and draft the matching document, in response to a chat message. No custom code is required to set up an agent; the configuration happens through Raven's interface.

Permissions are enforced at the user level, not the agent level: an agent only has access to what the person operating it in that conversation is already permitted to see or create. If a user can't create a specific document type, the agent acting on their behalf can't either — this scoping is what keeps agent permissions from silently exceeding a human user's actual access.

Skimmable summary: Raven AI agents run on OpenAI's Assistants API through a no-code setup, can create records or read receipt/invoice images, and inherit the permissions of whichever user is operating the agent — no separate agent-level access exists.

Can Raven run without sending data to OpenAI?

Raven can run without sending data to OpenAI or Anthropic by using a local LLM through Ollama, which you self-host on your own infrastructure — including on a server you control, such as an AWS instance you manage yourself. This is the option that matters for teams where data privacy is a hard requirement, since the AI agent then runs entirely against a model you host rather than a third-party API.

The trade-off is real and worth stating plainly: self-hosted open models available through Ollama are generally less capable than the latest cloud-hosted Claude or GPT releases, so choosing local-only is a genuine capability-for-privacy trade, not a free substitute. Testing against your actual use cases before committing either way is worth the time.

Skimmable summary: Raven's Ollama support lets you run AI agents against a self-hosted local model instead of a cloud LLM, trading some capability for keeping all data on infrastructure you control — a real trade-off, not a strictly better option.

How do I set up Raven on my ERPNext instance?

You set up Raven by installing it as a Frappe app on your existing ERPNext bench (self-hosted) or through the Apps tab on Frappe Cloud, after which channels and direct messages work immediately with no further configuration. Enabling the AI agent layer is a separate step: you connect an OpenAI API key (or configure Ollama for a local model), then define agents with specific instructions and scope them to the ERPNext DocTypes they should be able to touch.

Skimmable summary: Raven installs as a standard Frappe app with chat working immediately; AI agents need a separate LLM connection (OpenAI key or Ollama) and explicit DocType scoping, tested on staging before granting write access on a live instance.

Frequently asked questions

Is Raven free to use with ERPNext?

Yes — Raven is free and open source, with no licence fee, consistent with the rest of the Frappe ecosystem. If you connect a cloud LLM like OpenAI for the AI agent features, you pay that provider for usage; Raven itself doesn't add a cost.

Do I need coding experience to set up Raven's AI agents?

No — agent configuration in Raven is designed to be no-code, done through Raven's own interface rather than requiring custom Frappe app development. Connecting an LLM API key and scoping agent permissions to specific DocTypes is a configuration task, not a development one.

Can Raven agents access data I don't have permission to see?

No — Raven agent permissions are scoped to the user operating the agent in a given conversation. If that user doesn't have access to create or read a specific document, the agent acting on their behalf doesn't either, which limits how much an agent can do regardless of how it's instructed.

Is Raven the same as ERPNext's other AI features, like Frappe Assistant Core?

No — they're separate tools solving different problems. Raven is chat-native, with AI agents that act inside a conversation; Frappe Assistant Core connects ERPNext to Claude or ChatGPT over the Model Context Protocol for natural-language querying and reporting outside of a chat interface. Many ERPNext AI setups use both together rather than choosing one.