Wordware

Wordware's core editor lets users define AI agent logic using structured natural language in a document-like interface. Instead of writing Python or JavaScript, users compose prompts, define variables, and set up control flow using readable English instructions. This approach makes the logic transparent and editable by anyone on the team, regardless of technical background.

Workflows can leverage multiple LLM providers including GPT-4o, Claude, Gemini, and open-source models. Users can switch between models at any point in a workflow without restructuring the underlying logic, enabling quick A/B comparisons and cost optimization. This provider-agnostic design protects teams from being locked into a single AI vendor.

Any workflow built in Wordware can be deployed as a production REST API endpoint with a single click. The platform handles hosting, scaling, and endpoint management, removing the need to provision servers or set up cloud infrastructure. This dramatically shortens the cycle from working prototype to production-integrated service.

Multiple team members can simultaneously edit AI agent workflows in real time, similar to collaborative document editing. Every change is tracked with built-in version control, allowing teams to review prompt history, compare versions, and roll back to earlier iterations. This makes it possible for engineering and business teams to co-develop AI applications in a shared workspace.

Wordware supports conditional branching and iterative loops within agent workflows, enabling complex multi-step reasoning and decision trees. Users can define if/else conditions, loop over data sets, and chain multiple LLM calls together—all expressed in natural language. These constructs bring programming-level control flow to a no-code environment, supporting workflows that go well beyond simple single-prompt interactions.