SaaS · Enterprise Platform

A8 Essential

Redesigning an AI-powered data platform so enterprise teams could go from raw data to actionable insight — faster, with less friction.

My Role Lead Product Designer

Company Red Baron Pvt. Ltd.

Type Enterprise SaaS · AI Platform

Duration 2023 – 2025

Tools Figma · FigJam · Maze

A8 Essential dashboard — data upload and insight interface

Overview

The Problem Enterprise teams struggled to extract insights from unstructured data, leading to slow decisions and underutilised AI capabilities.

My Role Lead Product Designer — end-to-end design from research and problem framing through to final component handoff.

Tools & Methods Figma, FigJam, Maze, User Interviews, Competitive Analysis, Design Systems

Impact Improved conversion, reduced time-to-insight, and increased user engagement through a more efficient data-to-insight workflow.

Context

The Background

A8 Essential is an enterprise SaaS platform designed to help organisations surface insights from large volumes of unstructured data using AI-assisted workflows. When I joined the project at Red Baron Pvt. Ltd., the product had core AI capabilities but the interface was not keeping pace with user expectations.

Enterprise users — typically data analysts, operations managers, and C-suite stakeholders — were navigating a fragmented workflow that required too many context switches, too many manual steps, and offered too little feedback on what the AI was doing under the hood.

"The AI is powerful, but I can never tell what it's doing — or why it gave me this result."

This was the most common sentiment we heard during initial user interviews. Trust, transparency, and speed were the three pillars we had to design around.

Challenges

What We Were Up Against

Opaque AI Output

Users had no visibility into how the AI arrived at its conclusions. The result was distrust — leading to manual re-verification of every AI output, defeating the purpose of automation.

Fragmented Workflow

The journey from uploading data to generating an actionable insight spanned multiple disconnected screens, forcing users to lose context and restart frequently.

No Progressive Disclosure

Power users and occasional users were shown the same dense interface. There was no way to surface only the most relevant information at the right moment in the workflow.

Step 01 Research & Discovery Conducted 12 stakeholder interviews, shadowed 4 analyst workflows, and ran a competitive audit across 6 enterprise data platforms. Mapped friction points on a journey map.

Step 02 Systems Mapping Built a service blueprint spanning the full data ingestion → AI processing → insight delivery loop. Identified 11 redundant steps that could be collapsed or automated.

Step 03 Design & Iteration Ran 3 rounds of prototype testing using Maze. Iterated on information architecture, AI explainability patterns, and progressive disclosure controls before finalising handoff.

Solution

What We Built

The redesigned A8 Essential introduced a unified workspace model — a single canvas where data ingestion, AI processing, and insight delivery happen in one coherent flow. Users see real-time status of AI operations with plain-language summaries of what the model is doing and why.

We introduced a progressive disclosure pattern: casual users see a simplified "insight card" view, while power users can drill into the raw data pipeline, tweak parameters, and inspect individual AI reasoning steps.

A persistent action rail keeps the most frequent operations — run, compare, export, share — within one click at all times, regardless of where in the workflow the user sits.