Imagine for a second

You’re an attorney chasing an insider-trading trail. It’s 9 p.m. in a windowless war-room; the fluorescent lights hum, your coffee is lukewarm, and tomorrow’s partner briefing looms.

  • Slack exports dump into one massive JSON—timestamps locked to UTC.

  • iMessage spits out eight-hour chat slices in PST, each with a different file name.

  • Phone-call logs arrive as bare-bones CSVs—no timezone, no caller labels.

  • Discord threads hide buy signals behind sushi emojis.

  • A dozen cryptic emails—“buy the red balloons?”—might be the smoking gun, but they sit in yet another export folder.

The caffeine crash is coming, the partner wants answers by dawn, and the story you need is buried under a mountain of mismatched files.

Note : All case-study content—including images—has been carefully redacted or AI-generated for confidentiality.

Traditional E-discovery App

Problem: Fragmented Communications in Investigations

This scenario is common in heavily regulated fields like finance and law. Electronic evidence is no longer just emails and PDFs – it’s Slack threads, text messages, Teams chats, and more.

Unfortunately, legacy review tools weren’t built for these “modern” data formats. Reviewers like Maya end up manually reconstructing timelines by jumping between files and applications.

As one eDiscovery expert put it, “ [Industry leading app] was a complete nightmare…there are currently no application out there that handles message data well”.

Without specialized tooling, reviewing and reconstructing a full conversation from chat exports is complex and time-consuming

Important context can slip through the cracks, and every delay raises the risk of missing a crucial detail or misinterpreting a coded message.

Note : This is an AI-generated image

Vision: All in one Modern Viewer

We recognized the pain and formed a vision to modernize the review experience for these new data types. The goal was clear but broad: “Make it as easy to review Slack chats and text messages as it is to review emails.” In other words, create a Modern Viewer that could unify fragmented communications and even device status regards application into one coherent, chronologically ordered view. The challenge for our team was how to turn this vision into a practical, intuitive feature that meets heavy regulated industry needs.

LLM Generated mock

Dispel blindspots and internal assumptions

Before a single pixel was drawn, I ran a Multi-layer discovery to validate the vision, benchmark the market, and map technical reality.

Competitive Landscape, Finding the White Space.

What we saw in e-discovery land

  • Relativity Short-Message Viewer: great at showing Slack threads—but only after you run a heavy RSMF conversion and still one platform at a time.

  • Everlaw, Logikcull, DISCO: each promised “chat review,” yet the UI collapsed entire days into one document; cross-platform context vanished.

What we saw outside the bubble

  • Front, Shift, Trillian: slick omni-inboxes that merge Slack + email + SMS for live customer support. Inspiring—but they stay conversation-centric and ignore legal metadata.

The AHA! Moment

“What if we flip the axis—treat every single line as a document?”

By unifying chats into one-line records we could:

  1. Thread anything with a timestamp—Slack joke, Teams emoji, or phone-call note—into one scrollable story.

  2. Drop the new UI straight onto our existing table schema—no database surgery, no late-night migrations.

  3. Lego-stack future sources (Bloomberg, Discord, Voicemail) by just adding parsers, not rebuilding the viewer.

Why it matters

  • Developers loved the zero-overhaul path; utilize existing architecture.

  • Reviewers finally got a single narrative that survives platform‐hopping (“Slack ⚡ 09:00 → Email ✉️ 09:05 → iMessage 💬 09:06”).

Client Listening Tour

The quickest way to design enterprise tools — pick up the phone. We scheduled calls with litigation partners, corporate investigators, and expert reviewers from dozens of client firms. Each session mapped:

  • What data they collect (Slack, WhatsApp, Bloomberg, Cellebrite)

  • Which tools they juggle (Relativity, Concordance, Excel timelines).

  • Where it breaks: “Conversation exports force us to merge threads by hand; one missed timestamp and the story dies.”

Design Synthesis — From Messy to whole

Empathize → Define

Ran a taxonomy card-sort with reviewers and data engineers, clustering 50 real Slack, SMS, and email records; this surfaced the mental buckets of Context → Evidence → Forensics and let us anchor the UI hierarchy to users’ natural scan path—reducing cognitive load by exposing only the metadata they consult first.

Ideate

Framed the viewer around Context First, Details on Demand. Each line shows sender avatar, original platform styling, and a sticky date banner—giving instant “who / when” recognition. Hover states are user-configurable: a fraud analyst may surface IP address and device-status, while a litigation reviewer might show custodian or privilege flags. Conversation breaks and coloured edge bars mark channel shifts, yet forensic elements—read-receipts, emojis, edit flags—share a unified set of design elements to minimize cognitive load and keep attention on the narrative, not the UI. This balance of authenticity plus visual harmony became the guiding North Star

Prototype & Demo

Built an interactive Figma prototype and ran live demos for Am Law 100 firms, a global-bank compliance group, and two federal agencies—walking them through hit-highlight search → timeline scroll → hover-metadata reveal → inline tagging/redaction → one-click export.

The response was immediate: 100% attendee opted into the beta on the spot.

Feedback & Refinement

Add stronger visual breaks between conversations to avoid context bleed.

  • Surface a toggle for “Chronological view” vs “Conversation view” to aid focused review.

  • Clarify where de-duplication fits (flagged for version 2).

Those insights shaped the final design: we introduced conversation separators, a view-mode switcher, and documented a V2 dedupe workflow—ensuring the Modern Viewer met real-world reviewer needs while keeping the wow-factor intact.

Interactive Prototype Available Upon request

Outcome & Reflection

Modern Viewer launched as part of a major platform update, addressing one of the most painful parts of regulated data review: reconstructing fragmented, cross-platform conversations. Early adopters—spanning Am Law 100 firms, federal agencies, and global compliance teams—unanimously opted into the beta and praised the seamless integration, reduced onboarding friction, and intuitive experience.

Impact at a glance:

  • Up to 30% faster review time in mixed-data investigations by eliminating tool switching, time-zone juggling, and manual timeline assembly

  • Fewer tagging and timeline errors, thanks to structured metadata and live context preview

  • Clearer audit trails, with export-ready conversations in a single, narrative flow

  • Higher user comprehension, helping analysts catch subtleties like coded language or timing gaps

This project began with a vague request to "fix chat review," and through a research-driven, design-thinking approach, became a feature that delivers clarity, confidence, and control. It was a true fusion of business analysis and UX—translating user pain into elegant interaction patterns, under tight regulatory and technical constraints.

Thank you for reading. If you’d like to explore the full prototype or see how this vision became reality, I’d love to walk you through it.