Memotron - Digital memory atlas

A digital atlas for memory that helps users capture,
curate, and connect knowledge seamlessly across devices

Case Study Cover

Case Study Cover

My role
My role

Sole Product Designer - Feature Scoping, User Research, Interaction Design, Prototyping, UI Design

Team

Aravind - Founder & Engineer
Fuzail - Engineer

Timeline

Feb 2024 – Present

01/06

Context

Our digital lives are full of fragments, quotes, thoughts, articles, voice notes, bookmarks and and many more. Remembering them isn’t like keeping a diary. We weren’t trying to build just another note-taking app. We began by asking:

Our digital lives are full of fragments, quotes, thoughts, articles, voice notes, bookmarks and and many more. Remembering them isn’t like keeping a diary. We weren’t trying to build just another note-taking app. We began by asking:

What would it take to design a memory system that feels as natural as remembering itself?

That question arose not from a missing feature, but from observing persistent invisible friction in user’s workflows. We’ll go deeper into that problem next.

This case study focuses on the desktop app, with the same design principles carried over to mobile

02/06

Problem

Most tools in the PKM space weren’t designed as memory systems they grew feature by feature, often driven by user requests. That’s where the gap begins. From early user interviews, usage tracking, and friction logs, these recurring issues surfaced:

  • Capturing ideas often took too many steps, especially in spontaneous moments.

  • Organizing information demanded constant setup, leaving users managing their systems instead of their thoughts.

  • Linking ideas was shallow limited to tags or mentions making it hard to form deeper relationships

03/06

Tracing the Gaps

Desk research + Interviews + Competitor Analysis

Desk research + Interviews + Competitor Analysis

To move from assumptions to insight, we mapped the ecosystem of tools, behaviors, and user pain points through interviews, community research, and competitor audits.

We wanted to understand why these breakdowns kept recurring across tools and what it would take to solve them at a system level?

The wholesome chart began as a way to compare features across PKM tools. It helped us see where existing products overlapped and where gaps left room for something new.

Interactive wholesome chart (embedded from the Memotron site)

Interactive wholesome chart (embedded from the Memotron site)

04/06

The Shape of Memory

Our goal is to establish Memotron as a foundational system for digital memory. After understanding how memory breaks down, we defined three essentials for effective memory: capture, curation, and retrieval.

Cognitive framework of memory

Cognitive framework of memory

NCCL System

The process of capturing information can be cumbersome, and retrieval often falls short. However, the biggest challenge lies in curation; it can become a tedious task or be confined within rigid systems. This realization prompted us to rethink the entire structure of digital memory. Our exploration led us to develop the NCCL system architecture - a flexible framework built around four layers: Nodes, Collections, Combinations, and Linking

The foundational flow of Memotron

The foundational flow of Memotron

Node

We intentionally called them Nodes, not notes/pages. Because a node can be anything, such as a voice snippet, a screenshot, a photo, Markdown, or a video. We didn’t want to prioritize one format over another, because every kind of memory deserves equal weight. Because a thought isn’t always something you write, sometimes it’s something you say, hear, or capture without words.

From capture to Node

From capture to Node

Collections

Not everything requires a structured approach from the beginning. That’s why we created three flexible types of Collections:

Simple: No setup required. No properties needed. Just add nodes freely.

Typed: Introduce structure with properties as your memories begin to form patterns.

Query: Establish the logic once, and allow your memories to organize themselves as they expand.

A quick look at how Collections work

A quick look at how Collections work

Combinations

Combinations are a mechanism to combine various items that are frequently accessed together.

This feature will be launched in an upcoming update

Linking

We didn’t view linking as a form of navigation; rather, we saw it as a way to curate information. While most tools rely on inline mentions constrained to text, we developed direct linking that allows users to connect a node to its destination without having to open new tabs or interrupt their flow.

We took linking a step further with nodularity: the capability to attach new information to any part of a node, even down to a specific Markdown block or a passage deep within a lengthy manuscript.

To add depth to those links, we introduced Relations, enabling users to define the type of connection between ideas, similar to how they naturally think about context, cause, or meaning.

Uff. Sounds like a lot? But once you start using linking and layering, it all falls into place! 😅

A quick look at how linking works

A quick look at how linking works

05/06

In Their Words

From our users

From our users

06/06

Impact

  • Following its launch in November 2024, Memotron saw over 15,000 users sign up within six months

  • Achieved 3x growth in monthly active users within the first six months

  • Average session duration increased by 35% after targeted onboarding and workflow optimizations.

  • Active users across 20+ countries

  • Users completed more captures per session after the introduction of our fastest capture workflow

Linking

We didn’t view linking as a form of navigation; rather, we saw it as a way to curate information. While most tools rely on inline mentions constrained to text, we developed direct linking that allows users to connect a node to its destination without having to open new tabs or interrupt their flow.

We took linking a step further with nodularity: the capability to attach new information to any part of a node, even down to a specific Markdown block or a passage deep within a lengthy manuscript.

To add depth to those links, we introduced Relations, enabling users to define the type of connection between ideas, similar to how they naturally think about context, cause, or meaning.

Uff. Sounds like a lot? But once you start using linking and layering, it all falls into place! 😅

Glad you made it to the end!

Let’s create something amazing together.

Glad you made it to the end!

Let’s create something amazing together.

Glad you made it to the end!

Let’s create something amazing together.

Glad you made it to the end!

Let’s create something amazing together.