A Case Study on an Analogue Schematic Design Tool

In fast-moving engineering organisations, designers need tools that simplify complex workflows — here's how we designed a browser-based schematic editor with AI-assisted suggestions for analog engineers, and what we learned.

Impact at a Glance

  • 40% reduction in average workflow time for schematic edits
  • 60% increase in real-time collaboration sessions per project

The Challenge

User research identified three critical pain points in how engineering teams were working:

  • Fragmented toolchains: Separate applications for drawing, simulation, and review — with no continuity between them
  • Cluttered dashboards: Steep learning curves that discouraged new team members
  • No live visibility: No way to see teammates' edits or AI recommendations in real time

The objectives were clear: accelerate onboarding by 50%, reduce clicks per task by 30%, and embed AI and collaboration directly into the canvas — not as separate tools bolted on afterwards.

Research & Information Architecture

Competitive analysis surfaced gaps in analogue-first workflows and collaboration among leading EDA tools. Two core personas emerged — the Design Engineer and the Verification Engineer — each with distinct journey patterns and friction points.

The resulting IA placed everything within a three-panel canvas:

  • Left panel: Component library with search and filter
  • Centre canvas: Dot-grid schematic with multi-cursor and AI overlays
  • Right overlay: Slide-in panel for properties, AI suggestions, DFM warnings, and comments

Wireframes & Prototyping

Low-fidelity sketches validated layout, whitespace, and core flows — draw, connect, invoke AI. Mid-fidelity Figma prototypes then refined overlay behavior and contextual right-click menus. Slide-in overlays were a deliberate choice to surface deep settings without permanently cluttering the canvas.

Visual Design

The visual theme drew on a dark-green PCB-inspired palette with frosted glass panels over a dot-grid background — immediately legible to hardware engineers while feeling modern. WCAG 2.1 contrast compliance was maintained throughout. Microinteractions — hover and press states on toolbar items, AI confidence badge tooltips — were added to make the tool feel responsive and alive.

Collaboration & AI Integration

Real-time cursors and avatars show live edits directly on the canvas. The AI Suggestions toggle uses a confidence badge and a "Why?" tooltip that explains each recommendation in plain language — building trust without requiring engineers to blindly accept suggestions.

Inline overlays highlight optimisation opportunities without interrupting workflow. The AI is always visible but never in the way.

Testing & Iteration

Moderated usability sessions measured task times and error rates. A/B tests compared slide-in overlays versus persistent sidebars — slide-ins improved access speed by 25% and were strongly preferred by users who wanted to stay focused on the canvas. Post-launch analytics on feature activation and collaboration patterns guided further refinements.

Results

The MVP delivered 40% faster workflows, 60% more collaborative sessions per project, and high user satisfaction with both the onboarding experience and the AI transparency model.

Roadmap next steps include extended AI-driven DFM and yield checks, executive KPI dashboards, and a SPICE-deck sync plugin.

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