Case Study — Enterprise AI
Elevating an AI workspace: one input, every model.
A full architectural redesign of an enterprise-grade AI chat interface — transitioning a disjointed legacy system into a cohesive, input-first workspace that streamlines model selection, prompting, and output analysis for the User.
S
Saif Khan
Product Designer
·
2026
·
Web Application
Role
Product Designer
Scope
IA · UI · Interaction
Platform
Web Application
Fig. 1 — The redesigned workspace: a unified input container with chronologically grouped history.
Problem. The legacy interface suffered from fragmented information architecture. Model cards occupied the central canvas, obstructing the primary task flow, while the input field sat detached at the bottom of the viewport.
Goal. Replace the cluttered, card-dominated layout with a minimalist, input-first environment. Every architectural decision was measured against a single criterion — reducing cognitive load between the User’s intent and the system’s response.
01 — Legacy Audit
Three points of friction.
A full-surface audit of the legacy product narrowed the experience down to three structural problems, each pulling attention away from the prompt itself.
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Isolated input zone detached from primary controls
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Static model cards obstructing the workflow
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Undifferentiated chat history lacking semantic grouping
Fig. 2 — Legacy system: center-screen model cards and flat, ungrouped history.
02 — Architecture
Architectural consolidation and input focus.
Center-screen model cards were eliminated in favor of a unified input container anchoring the canvas. Model selection, attachments, and voice controls consolidated into a single component. Chat history moved into a structured sidebar with chronological grouping, enabling the User to locate prior sessions through semantic date clusters rather than linear scanning.
03 — Model & Voice
Dynamic model selection and multimodal input.
An in-line model switcher with integrated search surfaces the full model catalog without leaving the input context. Voice input renders as a live waveform contained directly within the primary field — recording, duration, and dispatch controls occupy the same footprint as text entry, eliminating modal interruptions.
Fig. 3 — In-line model switcher with search, and the voice waveform contained within the primary input field.
04 — Navigation
Collapsible navigation and contextual controls.
A multi-tier collapsible sidebar system maximizes screen real estate: navigation compresses to an icon rail, and the history panel collapses independently. Contextual hover menus expose pin, edit, and delete actions per conversation. A sequential prompt timeline panel on the right edge provides instant navigation across long sessions.
Fig. 4 — Collapsed icon rail, expanded first-tier navigation, contextual hover menu, and the sequential prompt timeline.
05 — Observability
Tabbed data visualization and observability.
Complex AI outputs segment into three distinct views: Answer renders structured content including comparative tables; Sources exposes clickable reference links for verification; Details surfaces execution metadata such as runtime and model attribution — giving the User full observability without visual overload.
Fig. 5 — Segmented output tabs: structured Answer view alongside execution Details.
06 — In Practice
In AI tooling, restraint is a feature: every removed element returned focus to the core exchange between prompt and response.
07 — Takeaways
Minimalism as utility.
Centralizing controls into a single input container aligned the interface with enterprise software standards and measurably accelerated workflows for the User. The redesign demonstrates that every element removed from the canvas returned attention to the work itself.