Dela AI Chatbot
Overview
Enterprise SaaS platforms often contain complex workflows and large feature sets, making it difficult for users to quickly find the functionality they need.
To address this challenge, I designed Dela, an AI-powered assistant that helps users navigate the product, discover features, and complete tasks more efficiently.
The goal was to reduce friction in complex workflows by providing contextual guidance and intelligent suggestions directly within the product experience.
Problem
Users of enterprise workforce management software often struggled to navigate complex workflows and locate the features they needed to complete tasks.
Key challenges included:
large product surface area with many features
difficult feature discoverability for new users
time spent navigating multiple screens to complete tasks
As the product grew, these issues created friction that slowed productivity and increased the learning curve for new users.
The product team saw an opportunity to introduce AI assistance to simplify navigation and support users directly within the application.
Constraints
Designing the AI assistant involved several constraints:
the assistant needed to integrate seamlessly within the existing product interface
users needed to trust AI-generated responses
the assistant had to support a wide range of workflows across the platform
the design needed to avoid overwhelming users with unnecessary interactions
The experience had to feel helpful and contextual, not intrusive.
Strategy
Instead of building a standalone chatbot experience, I focused on designing an embedded AI assistant that integrates directly into the product workflow.
The assistant enables users to:
ask questions about the product
locate features quickly
receive contextual suggestions for completing tasks
By embedding AI assistance within the interface, users could access help at the moment they needed it without leaving their workflow.
Process
Understanding user needs
I worked with product stakeholders to identify the most common situations where users needed assistance navigating the platform.
We discovered that users frequently needed help with:
locating specific product features
understanding available actions within a workflow
navigating between related sections of the product
These insights helped shape the core capabilities of the assistant.
Designing the Conversational Interface
I designed a conversational interface that allows users to interact with the assistant using natural language.
The assistant provides responses that guide users toward relevant product features and workflows.
The design emphasizes clarity and simplicity so users can quickly understand the assistant’s recommendations.
Integrating AI Into the Product
Rather than creating a separate help experience, the assistant was integrated directly into the product interface.
This allowed users to access guidance without interrupting their work or switching contexts.
The assistant acts as a navigation and discovery layer for the product.
Iteration and Collaboration
Throughout the project, I collaborated closely with product managers and engineering teams to refine the assistant’s capabilities and ensure the experience aligned with the underlying AI system.
Design iterations focused on improving clarity, usability, and the relevance of AI responses.
Outcome
The AI assistant provided users with a faster way to navigate the product and discover features without manually searching through menus or documentation.
Users could interact with the assistant to quickly find relevant functionality and complete tasks more efficiently.
Impact
The introduction of the AI assistant helped:
simplify navigation across a complex enterprise product
improve discoverability of key features
reduce friction for new users learning the platform
The project also helped establish patterns for integrating AI-powered assistance within the broader product ecosystem.
