Next-Gen AI for smarter workflows

Next-Gen AI for smarter SaaS workflows

You’ve heard of AI-powered text generators like ChatGPTβ€”now imagine AI that generates workflows instead of just words. As part of GEP’s mission to become an AI-first SaaS company, I designed an AI-powered search and intake orchestration product that’s transforming how businesses streamline decisions and workflows.

Beyond Text Generation: AI That Orchestrates Workflows

Beyond Text Generation: AI for SaaS That Orchestrates Workflows

Task completion time reduced by 40% for users thus boosting process efficiency & compliance.

User adoption increased 2x.



πŸš€ Impact:

Lead Product Designer

Product Designer

UX Researcher

AI, VP

Data Scientist

Engineering Lead

Engineering Team

Sr. Director, Product

Sr. Product Manager

Product Manager

Team:

Crafting the new AI first product landing page

Simple and easy cross app search experience, with internal and external source citations.

Let AI do the heavy lifting for you proactively!

Your everyday digital workspace reimagined.

Multitask with split screen conversational AI and Document view

Defining AI Touch-point & Components in Design System

16 column grid

Defined Flexible Grids for best readability in text heavy screens

πŸ” The Problem : Why Current Workflows Needed To Evolve

Users struggled with fragmented, inconsistent cross app search experiences

Finding the right information required manual effort & multiple tools

AI-powered search had potential, but trust & accuracy were key concerns


πŸ‘₯ Understanding Users and Their Pain-points

Casual Users β†’ Want quick, relevant answers with minimal effort

Power Users β†’ Need control, filters, and deep search capabilities

Procurement Teams β†’

Must evaluate options & simplify purchasing decisions


🚧 Challenges

AI recommendations needed to balance speed, accuracy & transparency

Users needed control over filtering, refinement & customization


By collaborating with AI Engineers, PMs, Data Scientists, and SMEs, I analyzed the product structure and identified key UX improvement areas: chat sessions, intent assessment, and response orchestration.

Understanding user intent and designing for key prompts was crucial. My fellow designer and I often wrote dialogues or role-played to capture the right sentiment and tone for an engaging experience.

I need to purchase laptops for my team.

What are my savings opportunities this week?

What Invoices are pending my approval today?

I was notified that my requisition was rejected. What can I do?

How do I download a copy of my Invoice?

Designing the "Front Door" bot response was crucial for accurately capturing user intent and key business nuances like function, delegation, and budget.

Outcome and Reflections

πŸ”„ What I’d improve next:

  • Making AI explanations even more interactive & customizable

  • Enhancing multi-modal search (text, voice, document parsing)

πŸš€ Impact

  • Task Completion time reduced by 40% for users boosting process efficiency & compliance

  • User adoption increased 2x.

πŸ“šβœ¨ Continuous Learning

Courses to Upskill

Conversation Design Institute β†’ Conversation Design

Google β†’ AI Essentials

Applying best practices from Industry leads:

Material Design’s Conversation Guidelines β†’ AI response structure

Salesforce Lightning β†’ Data-rich UI for business users

SAP Fiori β†’ Enterprise-level decision-making tools

Perplexity β†’ User interaction patterns for Search based AI products

Crafted with love.

Get in touch for full time roles or say hello at

ankita.dpande@gmail.com