Answers from your documentation
Connect the assistant to the agreed documentation sources and evaluate representative questions before launch.
Integrate AI chat and search into your documentation.
We deploy and configure Biel.ai within your documentation experience. The engineering scope covers the content connection, site integration, an agreed evaluation set, and a process for reviewing answer gaps.
Biel.ai is a product we own. Its subscription is separate from Studio’s integration work.
Custom AI bots tailored for your documentation
Connect users to answers drawn from your documentation and review questions that expose content or retrieval gaps.
Context-aware chatbots
Review answer relevance and source support against your chosen questions, content, and product versions.
Seamless integration
Implement the widget and search experience in your site, then validate the agreed reading and interaction paths.
Available in AI coding tools
Where your plan and access model support it, configure Biel.ai MCP access for compatible tools such as Claude Code and Cursor. Test source permissions, product/version context, and representative queries before handoff.
Integrations we can build
These platforms are examples for a fit assessment. We check content access, crawling or connector support, authentication, and site integration before committing to scope; listed systems are not all included in a package.
- Antora
- Docusaurus
- Gatsby
- HTML5
- Jekyll
- MkDocs
- Next.js
- NPM
- React
- Starlight
- Vue.js
- Sphinx
- Wordpress
- Confluence
- FreshDesk
- GitHub
- GitLab
- Notion
- Paligo
- Readme.io
- Zendesk
Transform your documentation with AI
Deploy the assistant within your documentation workflow and use interaction gaps to prioritize improvements.
AI expertise at your service
We scope the documentation sources, site integration, evaluation, and handoff around your requirements.
Seamless onboarding
We agree the access, configuration, launch checks, and operating responsibilities before implementation.
Flexible and scalable
Choose source coverage, access controls, usage limits, and operating responsibilities for the current requirement. Larger scopes may need a different product plan or additional engineering.
How it works, and what it costs
The assistant is powered by Biel.ai, a product we own. The hosted product subscription and Studio implementation are separate. MCP server deployment options are assessed separately from hosting the product itself.
The engine
Biel.ai
A separate subscription paid to Biel.ai. Compare current plans, usage limits, MCP availability, and private-source access on the product pricing page; we confirm the required plan during scoping.
The service
Integration & tuning
We connect agreed sources, implement the site or MCP integration, evaluate representative questions, and address selected retrieval or content gaps. Setup is quoted for defined scope; ongoing evaluation and improvements require a separate agreement.
Documentation teams we have worked with
Commonly asked questions
We agree the schedule after reviewing your content sources, site integration, access requirements, and evaluation scope.
Your team can manage the connected content and supported settings through Biel.ai. We document refresh behavior, ownership, and evaluation steps for your implementation.
We agree the indexed languages and evaluate representative questions in those languages. This service configures content retrieval and integration; any model training requires separate scope.
Review the query, interaction, and feedback signals available on your Biel.ai plan. We can define a review process for source gaps and unsupported answers; satisfaction metrics require an agreed measurement method.
From our blog
What we've learned deploying AI assistants on real docs sites.
We added an AI assistant to a docs site, tickets went up first
An AI assistant surfaced undocumented features support had been handling verbally. Documenting the gaps is what finally cut ticket volume.
Add an AI chatbot to your documentation
What it takes to put a reliable AI assistant in front of your docs, and where the real work is.
15 tips for better AI answers from your docs
Retrieval is the bottleneck before the LLM. Practical ways to structure pages so an AI assistant answers from them accurately.
Build your custom AI chatbot today
Share your content sources, reader or agent use cases, and access requirements. We will define integration scope, evaluation questions, and an operating process for reviewing unsupported answers.