Enfra

Designing AI Agents for non-technical teams

Timeline

2024, 5 months

What is Enfra?

Enfra’s AI Employee Builder platform aimed to enable non-technical users to create AI-driven “employees” tailored to their specific business needs. This was a zero-to-one project where I collaborated closely with Enfra’s founders to develop an accessible and powerful platform. The primary challenge was to design an intuitive experience that made complex AI functionalities easy to use for a non-technical audience.


My Role

Helped Enfra’s founders take the AI Employee Builder platform from concept to execution. My role encompassed strategic planning, defining a cohesive design language, and creating a scalable design system that integrated AI-driven components.

The Challenge

Enfra’s vision was to democratize AI by allowing users from various industries to deploy customized AI components without needing technical expertise. Key challenges included:

Making AI Accessible

Simplifying complex AI interactions to make the platform approachable for users with minimal technical background.

Simplifying complex AI interactions to make the platform approachable for users with minimal technical background.

Intuitive Configuration

Ensuring users could easily configure AI components to suit their business goals without feeling overwhelmed.

Ensuring users could easily configure AI components to suit their business goals without feeling overwhelmed.

Design Goals

User-Friendly AI

Create a seamless user experience that demystifies AI components and workflows.

Guided Interaction

Break down complex processes into clear, manageable steps to boost user confidence and success.

Strategic AI Integration

Worked with the founders to strategically embed AI throughout the platform. We defined critical points where AI-driven decision support and automation could directly impact user productivity.

Simplifying Complex AI Interactions

Designed a user interface that broke down the setup process into intuitive, guided steps. I incorporated instructional cues, tooltips, and modular templates to make AI features accessible to non-technical users.

Developing a Cohesive Design Language

Created a design language that highlighted AI-driven actions with visual cues, such as icons and micro-interactions, that guided users through the process and enhanced engagement.

Establishing a Scalable Design System

Built a modular design system with reusable components that could support future expansion, ensuring the design remained consistent as new features were added.

The final design delivered a comprehensive platform that allowed users to configure and deploy AI employees through a series of guided workflows:

  • Define Goals: Users specify the business outcomes they want from the AI employee, using straightforward language and guided prompts.

  • Configure Parameters: Users select and customize AI components (e.g., chatbots, recommendation engines) with simple controls like sliders and toggles.

  • Deploy AI Employees: Users can deploy their configured AI components directly into their workflows, with real-time feedback on expected performance.

Outcome

High Adoption Rates: Feedback showed users felt empowered to configure AI-driven solutions without needing technical support. This led to a significant increase in user engagement and platform adoption.

Positive User Feedback: Users praised the clarity and accessibility of the platform, noting that they could focus on business outcomes rather than the technical complexity of setting up AI.

Reflection

This project strengthened my skills in designing accessible, AI-powered products and developing scalable design systems for complex domains. Working on Enfra’s platform allowed me to apply AI in a user-centered way, focusing on making advanced technology approachable and valuable to a broader audience. This experience has prepared me to bring impactful, AI-driven solutions to diverse industries.

Enfra Website ↗