Show HN: Strada – Cloud IDE for Connecting SaaS APIs
getstrada.com
While working on our first product (a unified accounting API), we learned that as companies grow, their integration teams become more technical but typically still use low-code tools. We also observed that as LLMs are becoming popular, these teams (usually outside of engineering) are adopting more code. For example, we spoke with multiple companies that generate integration code with an LLM and use it in their low-code platform.
Unfortunately, most integration tools are not designed with code as a first-class citizen. They often have limited support for external libraries, restrict how variables are used, and limit how code blocks interact with other workflow steps. But integration developers put up with them because stitching together authentication, scripts, APIs, infrastructure, and observability is time consuming and not a core focus for their teams.
Instead of drag-and-drop blocks, we chose code as the main interface. Tasks that are frustrating in low-code tools become simple with code: conditional logic with layers of branching, complex transformations, or problems that an external library already solves (for example, redacting personally identifiable information with the scrubadub library [1]). Each Strada workflow is a contiguous Python script, and every action configured in the UI can be invoked like a function. We started with Python since it’s popular with teams outside of engineering, like IT, Data, and Ops.
Our goal is to help integration builders focus on logic unique to their business by simplifying everything outside of that: - Integrations: we handle authentication and provide abstractions for common app actions; - Triggers: workflows can be triggered by a webhook or run on a schedule; - Infrastructure: one-click deployment with automatic scaling; - Observability: detailed logging of workflow actions, payloads, and errors.
Today, customers use Strada for workflows like Customer Support (receive Zendesk ticket webhook, remove sensitive information, perform sentiment analysis using OpenAI, and escalate problematic tickets) and Customer Onboarding (receive webhook with new customer data & files, transform to expected format, send request to third-party API, send request to internal endpoint).
What we're currently working on: - More enterprise app integrations; - A self-hosting option; - More runtimes in addition to Python; - AI for code generation.
We’re excited for you to try it and share your feedback!