Generate technical documentation from system descriptions. AI creates API docs, component specs, service maps, and infrastructure diagrams in Mermaid & PlantUML.
Sequence diagrams for REST, GraphQL, and gRPC endpoints with request/response flows.
Detailed component diagrams with interfaces, dependencies, and interaction patterns.
Visualize microservice dependencies, communication patterns, and failure domains.
Entity-relationship diagrams, schema documentation, and data model views.
Cloud architecture, container orchestration, and networking topology views.
All docs as Mermaid & PlantUML. Store in Git, review in PRs, diff over time.
Generate professional technical documentation with AI in three steps.
Provide technical details about your system, API, infrastructure, or process. Use precise engineering terminology and specifications that Cybewave's AI will structure into formal documentation.
The AI organizes your technical input into industry-standard documentation formats with appropriate sections, diagrams, code examples, and cross-references between components.
Download as markdown for Git repositories, export with diagrams as SVG or PNG, or generate a complete project ZIP ready for deployment to documentation platforms.
Generate comprehensive API documentation with endpoint descriptions, request and response schemas, authentication flows, error handling, and usage examples.
Produce detailed infrastructure runbooks covering deployment procedures, scaling operations, monitoring setup, and disaster recovery steps for your cloud architecture.
Create step-by-step deployment guides with architecture context, environment configuration, dependency management, and rollback procedures for every environment.
Build troubleshooting guides that map symptoms to probable causes using your system architecture, with diagnostic steps and resolution procedures.
Generate integration guides showing how external systems connect to your platform, including authentication, data formats, rate limits, and error handling.
Produce release notes that explain not just what changed but why and how changes fit into the broader system architecture for stakeholder understanding.
Technical documentation is often written once and never updated — AI generation makes it cheap to regenerate from current architecture diagrams, keeping docs current as systems evolve. When documentation costs hours of engineer time to produce, teams understandably deprioritize it. When it takes seconds, freshness becomes the default.
Stale technical documentation is worse than no documentation because it actively misleads. Engineers who trust outdated runbooks or API docs make incorrect assumptions that lead to outages and integration failures. AI-generated documentation tied to current architecture diagrams eliminates this dangerous gap between docs and reality.
Comprehensive technical documentation also reduces the bus factor across engineering teams. When critical system knowledge is locked in individual heads rather than written down, every departure or vacation creates risk. AI-generated docs make externalized knowledge the path of least resistance rather than an afterthought.
Architecture documentation
Design documents
Architecture specifications
Engineering-level docs
AI-generated arch docs
Diagrams from code
AI-powered modeling
Version-controlled diagrams
Free to start. 50 AI credits/month. No credit card required.
Get started for free →