As an AI Orchestration Platform that sees a future where AI can create completely functional solutions on behalf of its users, we see the attraction of ‘no code’ platforms. But even in that future, code is and does exist under the covers. The challenge with ‘no code’ approaches, especially in creating truly functional AI automation solutions, is they only get you so far. And it’s never quite far enough. This is especially true for highly scaled, critical enterprise AI solutions that enhance workflows, processes and tasks.

Drag a couple of boxes and you can have AI magically scrape a website, summarize the industry, push out a formatted data set and update it to Excel. It’s very cool, no doubt. It’s also very much a parlor trick. And like parlor tricks, they don’t actually provide value in the real world, where humans, distributed systems, distributed data sources, complex workflows, variable processes and existing enterprise platforms meet in the thick stew of reality.

No Code is short for basic functionality. It takes a relatively easy task (easy to define, easy to guardrail) and automates it. But the true value from AI systems isn’t basic. It isn’t enhancing or automating already easy tasks. That could already be done through RPA platforms like UI Path. It’s the hard stuff, the complex stuff, the deeply nuanced and variable stuff that will drive AI ROI.

But we also understand that developers will need to develop. (Contextual makes that easy too):

// Extract the response from the OpenAI API result
const response = msg.payload.choices[0].message.content;

// Retrieve the associated ID from msg
const associatedId = msg.associated_id;

// Save the original response to pass it through
msg.originalResponse = {
    response: response,
    associated_id: associatedId
};

// Prepare the payload for creating the new object
msg.payload = {
    response: response,
    associated_id: associatedId
};

return msg;

This is why, while Contextual is fully leaned into helping developers avoid tedious infrastructure, connection, integration, and data tasks, we recognize that a low-code environment that allows for … well …. software … is what enterprises actually need to deliver on AI solution value. Complex data analysis has to happen. Cross data searching is required. Multiple step workflows that don’t exist easily in a simple 3 steps on a chart are needed. By making those critical functions easier, Contextual makes AI solution creators 10x faster in creating a solution that matters.

If you’re a systems integrator, software engineer, digital agency or developer looking to deliver on the promise of an AI solution that actually transforms a business, you need the tools to make that happen. You don’t need to waste time on infrastructure, compute, databases, API layers, etc. You need to focus on business logic. But you also need to be able to make actual software. Not a fun to watch card trick. Contextual is your answer. We are empowering more people to do more and better, building products and solutions - software… not gimmicks.