Architecture overview
Guides Knowledge AI is a platform for building AI-powered knowledge assistants from your existing documentation. The diagram below shows the end-to-end architecture.
Guides Knowledge AI platform architecture
Content flows into the platform from two sources:
- AEM Guides — native DITA content with rich metadata (prolog, shortdesc, navigation titles) is indexed directly into the knowledge graph.
- External systems — content in HTML, Markdown, PDF, or DOCX formats is ingested through AI-assisted conversion pipelines that transform it into structured DITA before indexing. Metadata such as taxonomy and ontology information is preserved and used for entity extraction and retrieval.
Each domain (D1, D2, ... Dn) is an isolated knowledge container with its own knowledge graph, model configuration, indexed documents, and chat history. Domains let you organize content by product, team, or use case while keeping configurations and analytics separate.
Users and applications access domain knowledge through multiple channels:
- MCP — connect AI-powered developer tools (Cursor, Claude Desktop) directly to a domain. Also powers Adobe Brand Concierge for brand-aligned AI assistance.
- API — programmatic access via API keys for custom integrations and workflows. Includes Slack integration to bring Q&A into Slack channels for team collaboration.
- Chatbot widget — an embeddable widget for websites with configurable appearance and behavior.
The platform provides a broad set of tools for managing, optimizing, and monitoring your knowledge assistant:
- Analytics & Reports — usage trends, LLM latency, answer success rates, cache hit rates, and top users.
- Feedback — human feedback (thumbs-up/down) and LLM-as-a-Judge automated scoring, with side-by-side comparison.
- Prompt Management — customize answer generation and entity extraction prompts to tailor chatbot behavior.
- Golden Dataset & Evaluations — upload question-answer datasets, run experiments, and measure answer quality over time.
- A/B Testing — change a model, prompt, or retrieval parameter, then re-run an evaluation experiment against the same dataset to compare results side by side and find the best configuration for your domain.
- Content Optimization — AI quality scoring of indexed documents with per-criterion breakdowns and actionable suggestions.
- User Management & Security — custom roles with granular org-scoped and domain-scoped permissions, API key management.
- BYOM — Bring Your Own Model support for Azure OpenAI, WatsonX, and Gemini, with custom LLM, embedding, and evaluation model configurations.
FAQ
What is Guides Knowledge AI and what does its architecture cover?
Guides Knowledge AI is a platform for building AI-powered knowledge assistants from your existing documentation. Its end-to-end architecture spans how content is supplied into the platform, organized into knowledge domains, accessed through consumption channels, and managed through platform capabilities.
How does content get into Guides Knowledge AI from AEM Guides and external systems?
Content enters the platform from AEM Guides and from external systems. AEM Guides native DITA content with rich metadata is indexed directly into the knowledge graph. External content (HTML, Markdown, PDF, DOCX) is converted through AI-assisted pipelines into structured DITA before indexing, preserving taxonomy and ontology metadata for entity extraction and retrieval.
What are knowledge domains and what is isolated per domain?
A knowledge domain is an isolated knowledge container (D1, D2, ... Dn) used to organize content by product, team, or use case. Each domain has its own knowledge graph, model configuration, indexed documents, and chat history. This separation keeps configurations and analytics distinct across domains.
What channels can users and applications use to access domain knowledge?
Domain knowledge can be accessed through MCP, an API, or a chatbot widget. MCP connects AI-powered developer tools like Cursor and Claude Desktop to a domain and also powers Adobe Brand Concierge. The API provides programmatic access via API keys and includes Slack integration, while the chatbot widget is embeddable on websites with configurable appearance and behavior.
What platform capabilities are available to manage and improve a knowledge assistant?
The platform includes Analytics & Reports, Feedback (human and LLM-as-a-Judge), Prompt Management, Golden Dataset & Evaluations, and A/B Testing to compare configurations side by side. It also provides Content Optimization with AI quality scoring and suggestions, User Management & Security with granular permissions and API key management, and BYOM support for Azure OpenAI, WatsonX, and Gemini with configurable LLM, embedding, and evaluation models.