AI Blocks

Each block represents a discrete operationan LLM call, a web search, a database query, a data transformation, a conditional branchand users wire them together visually to define end-to-end AI workflows.

This visual approach makes AI pipeline construction accessible to domain experts who understand their use case deeply but lack the programming background to implement it in code.

The platform supports building a wide range of AI applications: document processing pipelines that extract and classify information, customer support automation flows that route and respond to queries, research assistants that search and synthesize from multiple sources, and content generation pipelines with review and approval steps.

Blocks for popular AI servicesOpenAI, Anthropic, Hugging Face models, vector databasescome pre-configured, and custom API integrations can be added for organization-specific data sources.

Business analysts, product managers, and domain experts who want to build AI-powered tools without depending on engineering teams use AI Blocks to prototype and deploy workflows independently.

Operations teams automating document-heavy processescontract review, report generation, data extraction from unstructured sourcesfind the visual workflow approach more maintainable than scripted automation when the business logic changes frequently.

The platform also serves as a rapid prototyping tool for ML engineers who want to test LLM pipeline architectures quickly before committing to a coded implementation.