What is Weam AI?

Weam is an open source platform that helps teams adopt AI systematically. It includes a complete, production-ready stack with Next.js frontend and Node.js/Python backend – ready to deploy and use immediately.

Why Weam?

Modern teams need easy access to the latest AI models. Weam connects to all major LLM providers out of the box – just add your API keys and you're ready to go. Think of it as ChatGPT built specifically for teams.

All your organization's AI interactions live in one centralized platform, organized into "Brains" (intelligent folders). These Brains contain not just chat histories, but also your custom prompts and AI agents. You can structure Brains around your departments – Marketing, Sales, Engineering, Support – whatever fits your organization.

Use Cases And Features

1. Prompt Library & Power Prompt

Weam AI provides a Prompt Library where teams can create, save, and organize prompts — complete with structured templates such as brand profile, product info, or company context. This supports consistent, high-quality outputs across all team members. Thanks to the "Fork Chat" feature, colleagues can share and reuse prompts, enhancing collaboration and reducing repetitive effort. Additionally, Power Prompt enriches basic queries by automatically adding context and important details, ensuring more accurate and polished AI interactions.

2. Pro Agents for Business Automation

Weam's Pro Agents are production-ready AI assistants tailored for common business needs. Examples include:

• Sales Call Analyzer — reviews and extracts insights from sales conversations or recorded calls.
• SEO Article Writer — generates SEO-optimized content in minutes.
• Business Proposal Writer — drafts polished proposals on demand.

These agents enable teams to automate routine tasks, save time, and focus on strategic work.

3. Document Upload & RAG Integration

Weam supports document upload (PDFs, DOCX) into chat sessions and agents, allowing AI to reference internal content dynamically via Retrieval-Augmented Generation (RAG). This means teams can feed their knowledge base directly into workflows, enabling agents to produce informed, contextually relevant outputs—perfect for generating summaries, answering questions, or drafting doc-based responses.