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Before diving deeper, it helps to understand the key concepts that make up the Brainstormer platform.

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Agents

An agent is your AI-powered conversational assistant. Each agent has its own personality, instructions, and capabilities defined by:
  • A system prompt that tells the AI how to behave
  • A selected AI model (GPT-4, Claude, Gemini, Llama, and more)
  • Optional knowledge bases that ground responses in your content
  • Configuration for streaming, temperature, and welcome messages
Agents can be in draft or published state. You test in draft mode and publish when ready to share.
Agents were historically called “bots” in the codebase. You may see both terms — they mean the same thing.

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Knowledge Bases

A knowledge base (KB) is a collection of content that your agent can search and reference when answering questions. Knowledge bases support:
  • Documents — PDFs, Word docs, text files, images, audio, and video
  • Web sources — URLs, RSS feeds, sitemaps
  • Social media — Instagram posts, YouTube videos, Twitter content
  • Platform connectors — Substack, Medium, Ghost, and other blog platforms
When you link a knowledge base to an agent, the agent uses RAG (Retrieval-Augmented Generation) to find relevant content chunks and include them as context when generating responses. This is what makes responses accurate and citable rather than purely generated. Each knowledge base also builds a knowledge graph — a network of entities and relationships extracted from your content that enables structured discovery alongside vector search.

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Prompts

Prompts are the instructions that control how your agent behaves. Brainstormer uses a unified prompt configuration system with several prompt types: Each prompt supports two modes:
  • Fixed — Static text that is used as-is (with variable substitution)
  • Generated — An instruction sent to the AI model, which generates the actual content dynamically
Prompts support dynamic variables using {{variable_name}} syntax, letting you personalize messages with user names, plan tiers, or any custom data. All prompt changes are versioned with semantic versioning (major.minor) and a full changelog, so you can track what changed and roll back if needed.

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Models

Brainstormer connects to 300+ AI models through OpenRouter, giving you access to providers like:
  • OpenAI — GPT-4, GPT-4o, GPT-3.5 Turbo
  • Anthropic — Claude 3 Opus, Sonnet, Haiku
  • Google — Gemini 2.0 Flash, Gemini Pro
  • Meta — Llama 3, Llama 2
  • And many more
Each model has different strengths, pricing, and context window sizes. You choose the model that best fits your agent’s needs — a fast, cheap model for simple Q&A, or a powerful model for complex reasoning. The platform syncs available models from OpenRouter automatically, so you always have access to the latest options.

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Organizations

An organization is your workspace in Brainstormer. Everything — agents, knowledge bases, conversations, and billing — is scoped to an organization. When you register, a default organization is created for you. You can:
  • Invite members to collaborate on agents and knowledge bases
  • Assign roles (owner, admin, member, viewer) to control what each person can do
  • Create groups to manage permissions for teams of users
  • Configure settings like approval workflows and API keys
Organizations are the unit of billing — credits are purchased and consumed at the organization level.

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Credits

Brainstormer uses a credit-based billing system to track and charge for platform usage. Here is how it works:
  • 1 credit = $0.50 (configurable by platform administrators)
  • Every external AI call (chat completions, embeddings, vector operations) incurs a cost
  • The platform applies a margin multiplier (default 2x) to the raw provider cost
  • Credits are deducted from your organization’s wallet automatically
For example, if an AI chat call costs $0.01 at the provider level:
  1. Charged cost = 0.01x2.0=0.01 x 2.0 = 0.02
  2. Credits burned = 0.02/0.02 / 0.50 = 0.04 credits
Your organization has a credit wallet that tracks your balance. All transactions are recorded in an immutable credit ledger for full auditability.
Credits cover all billable operations: AI chat completions, document embeddings, vector search queries, file storage, and voice synthesis. You do not need to manage separate billing for each service.

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How It All Fits Together

When a user chats with an agent:
  1. The agent’s system prompt is loaded and rendered with any dynamic variables.
  2. If knowledge bases are linked, the platform runs a semantic search across them.
  3. Relevant content chunks are injected into the AI context with numbered citations.
  4. The selected AI model generates a response grounded in your content.
  5. The response is streamed to the user with interactive citation tooltips.
  6. Credits are deducted from the organization wallet based on the provider cost.

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Next Steps

Creator Wizard

Build your first agent using the guided Creator Wizard.

Creating a Knowledge Base

Set up a knowledge base to ground your agent in real content.