Substrata

Bringing AI to the Surface – Designing Visible and Responsible Intelligence in Substrata for Dealmakers

Substrata is an AI-powered sales intelligence tool that analyzes communication data to reveal relationship insights. But for users, AI often feels invisible — its logic hidden, its results uncertain, its value unclear.

My goal was to design a transparent and responsible AI experience, one that shows how insights are formed, lets users stay in control, and builds trust without overwhelming them.

Period:

2024 - 2025, Freelance
2025 - Present, Part-Time

Deliverables:

Design System (50% adopted)
Gmail Extensions Redesign
LinkedIn Extension Design
Meeting Analysis Design
Dashboard Concept

Team:

2 Product Designers
5 Developers
3 Sales Managers (Demo Calls)
1 Product Manager
1 QA Engineer

Dark gradient background blending black into deep purple with faint star-like dots scattered.Open laptop displaying a sales dashboard with Substrata Assistant metrics, AI learning score, user profile, and upcoming meetings.

The Challenge:
making AI feel visible, guided, and human-owned

The main challenge was to design an experience that brings AI to the surface, helping users understand how intelligence works, stay in control of interpretations, and trust both the system and their own decisions. Charts and metrics lacked explanations or interpretation, leaving users unsure how insights were generated.

At the same time, the team avoided displaying AI reasoning out of fear that imperfect or biased conclusions might damage user trust.

Approach & Process:
From invisible AI logic to transparent, guided interactions

We analyzed how users engaged with AI insights and where trust broke down — most saw data, not reasoning. From these findings, I defined principles for explainable AI:

  • make reasoning visible (“why” behind insights)
  • let users guide or refine AI outputs
  • show uncertainty with visual cues

I created early wireframes and interaction flows that framed AI as a collaborative assistant, not an oracle - surfacing intelligence while giving users final ownership of interpretation.

Key Steps:
From Invisible Logic to Explainable AI UX

1. Problem Exploration

Identified where AI felt “invisible”, missing context, lack of explanations, and unclear reasoning.

2. Mapping Understanding Gaps

Traced how users interpreted signals and where they lost confidence or control.

3. Design Principles Definition

Defined rules for explainability, feedback, and shared control, AI should reveal its logic and invite user input.

4. Concept and Interaction Design

Prototyped AI reasoning with layered clarity, combining confidence cues and contextual hints

5. Validation and Iteration

Tested with internal teams to ensure the system communicates intelligence responsibly, avoids overpromising, and builds trust over time. The sales team shared demo recordings that helped us analyze user feedback, impressions, and recurring pain points.

Redesign Overview

The new interface combines conversational flow, contextual awareness, and transparent reasoning, helping users understand why suggestions are made and stay in control of outcomes.

By introducing visual cues for AI confidence, explanations for insights, and micro-feedback moments, the redesign turned the experience from automation that predicts into intelligence that collaborates.

This structure enables sales managers to work confidently with AI, interpreting signals, validating tone, and co-creating responses with full visibility and trust.

Bridge Redesign Overview

Cross-platform Design System

Unified Substrata’s platform and extensions (Gmail, Outlook, HubSpot, LinkedIn) under one consistent design language.
~50% product adoption, improved consistency, and reduced UI duplication.

Color palette table showing Tertiary, Success, and Information colors with corresponding text and container variants.

Extension Redesigns & New Builds

Redesigned and rebuilt Substrata’s extensions and Meeting Analysis tool for clearer guidance and consistent UI.

Added new visual models - timelines, graphs, and signal maps - to reveal interaction patterns.

Expanded AI from analysis to actionable guidance: next steps, tone suggestions, and deal strategies.

Created a shared workspace for managers and teams to review conversations, reports, and progress together

Two smartphone screens showing a cryptocurrency bridge app interface with options to select network and token, and fields to send and receive tokens with wallet address input.

AI Dashboard Queries

Designed a smart dashboard concept where users can ask AI for instant summaries, deal health updates, or insights across emails, meetings, and relationships.

AI highlights risks, opportunities, and next actions, helping users quickly understand what changed and what requires attention.

The dashboard also supports quick prompts, enabling fast follow-ups, meeting prep, or weekly summaries in one place.

Two digital dialog boxes showing a cryptocurrency transfer review and transaction status with steps for Sepolia Ethereum transfer and confirmation in progress.

Explainable AI & Feedback

Designed interaction patterns that let users understand why AI made a suggestion, how confident it is, and correct or refine interpretations directly in the flow.

User interface showing AI learning score at 72%, analytics of 3,400 emails and 123 meetings, and feedback section with thumbs up, thumbs down, a four-star rating, and a text box for comments.

Impact

~50%

faster workflow across Gmail/Outlook/HubSpot extensions

~50%

higher adoption of the new cross-platform design system

~30%

reduction in user confusion around AI suggestions (based on feedback)

~25%

faster meeting prep using AI summaries

Learnings:

Designing for both creativity and code

Creating the Haven1 design system reinforced that design isn’t just about aesthetics - it’s about building bridges between creativity and engineering.
Balancing visual clarity with technical precision allowed the team to ship faster while maintaining a cohesive product identity.
Extension Before & After Redesign
From Fragmented UI → to Native Gmail Experience
Two side-by-side screenshots of Gmail inboxes showing email conversations and Substrata email analytics and simulation tools.
Wizard Before & After Redesign
From interrupted flow - to AI chat bot
Side-by-side screenshots of Gmail inbox and email compose interface showing a sales email draft and a message wizard with options for follow-up or reply, alongside a Substrata for Email tool with features like simulator, X-Ray, and message analysis.
Redesign Extension
From interrupted flow - to AI chat bot
Five mobile screens of Substrata for Email app showing Signals tracking emails, detailed email opened view with tracking info, Analysis tab with authority zone and sentiment slider, Simulator tab with message pointers and authority change, and AI draft preparation for Authority Zone positioning.

Key Learnings

  • Trust in AI depends on visibility and explainability
  • Users engage more when AI invites discussion, not decisions
  • Feedback loops are critical for responsible AI
  • Native integrations drive adoption more than advanced features

What’s Next
Evolving AI-driven Product Systems

  • Deeper AI Feedback Loops - Expanding confidence indicators, explanations, and user corrections so AI continuously learns from real sales context.
  • Team-level Insights & Coaching - Turning individual analyses into shared team views: patterns across reps, coaching opportunities, and performance trends.
  • Smarter AI Queries - Enabling more natural, cross-data questions like “What deals need my attention today?” or “Why are negotiations slowing down this week?”
Designing an accessible Web3 portal by delivering a consistent UX and a scalable design system.