Austin-Based ChronoTracer Launches Legal Tech Platform to Automate Case Chronologies

A legal technology startup, ChronoTracer, is making its official launch today with the rollout of a platform designed to automatically convert digital evidence into searchable, filterable chronologies for litigation and investigation teams.

The Austin-based company was founded by former attorney Richard Gorelick, who started his career at Coudert Brothers before transitioning to technology, and software engineer Dexter Weiss.

The company addresses what Gorelick describes as a persistent inefficiency in legal practice — the manual creation of fact chronologies from voluminous digital evidence.

“Here they were,” he told me during a recent demo, describing the experience that led him to develop the platform, “a very sophisticated legal team working with an Am Law 20 firm, and they were cutting and pasting out of evidence stored in Relativity into a giant Excel spreadsheet.”

Filter and Search

Designed specifically to address this inefficiency, ChronoTracer imports digital evidence in virtually any format — including emails, phone records, text messages, social media posts, voicemails, financial records, and web search histories — and structures each piece into what the company calls “events” within a unified, time-ordered database. Users can then filter and search across all evidence types simultaneously.

The platform processes individual documents to extract multiple chronological events. For example, a single phone record or email thread can generate thousands of separate chronology entries, each tagged with timestamps, participants and metadata.

Key features include automatic translation and transcription services, event-level deduplication that goes beyond standard document-level deduplication, identity matching across different evidence sources, and integration with reverse phone number lookup services.

After leaving Coudert, Gorelick cofounded RGM Advisors, an AI-driven trading firm that was acquired by DRW in 2017. He and Weiss began developing ChronoTracer in late 2020, initially as a solution for a specific case before expanding it into a commercial platform.

“The future of evidence analysis isn’t just about reviewing documents — it’s about understanding what happened, quickly and clearly,” said Gorelick. “ChronoTracer restructures messy, fragmented evidence into a dynamic, easy-to-use chronology — helping legal teams see the full story and act on it with confidence.”

A Growing Field

In its launch announcement, the company claims to be “the first litigation and investigation software that automates case chronologies and accelerates fact analysis across virtually all types of digital evidence.”

It is certainly not the first to automate chronologies. In fact, the last year or two has seen the launch of a number of chronology-building tools, many leveraging generative AI to extract timeline information from documents.

However, Gorelick argues that many of the existing e-discovery platforms and chronology tools require users to build chronologies “backwards” — requiring them to identify key facts during document review and then construct timelines from tagged items.

“What we do is build an entire comprehensive chronology from all the evidence that we process and then make it very easy to filter and sort to get down to the events that meet your criteria,” Gorelick explained during the demonstration.

However, it may be the first to automate chronologies “across virtually all types of digital evidence.” Other products often are limited to certain types of evidence or certain types of digital information.

(Readers: Please fact check me on this.)

The company positions itself as complementary to, rather than competitive with, existing e-discovery platforms, working alongside systems such as Relativity and Disco, and able to accept data exports in various formats.

Key Features

Key features of ChronoTracer include:

• Automatic chronology building. Extracts events, participants and identifiers from virtually any volume or type of evidence.
• Powerful search and filters. Quickly surfaces events by participant, timeframe or type.
• Event-level insights. Interweaves events across documents to uncover the actual actions and interactions in a case.
• Translation and transcription. Automatically processes foreign-language and audio files.
• Deduplication and identity matching. Merges duplicate evidence (even from non-duplicate documents) at the event level and unifies identities across evidence.
• One-click source access. Navigate directly from an event to the underlying source file.
• Enterprise-grade security. SOC 2-compliant infrastructure with end-to-end
  encryption in a secure, single tenant environment.

Early Adopters

Gorelick said that ChronoTracer is already in use at Am Law 100 firms, NLJ 500 firms, and litigation boutiques. The platform has been tested on cases involving over 20 million files, the company said.

Use cases for the platform span the litigation lifecycle, Gorelick said, including early case assessment, case development and strategy, aligning timelines with witness statements and legal obligations, client and witness preparation, discovery and evidence organization, mediation and settlement support, and courtroom presentations.

Legal teams report using the platform to quickly answer fundamental case questions — who did what, when, and with whom—without manually extracting facts or managing evidence in spreadsheets.

One early use case involved a public corruption case with multiple defense teams, where the platform processed diverse evidence types including forensic phone records and cell tower data that required custom data pipeline development.

Pricing and Development

The company uses a pricing model combining setup fees based on evidence complexity and volume, plus monthly fees covering hosting, support, and training. Unlike some e-discovery platforms, ChronoTracer does not heavily weigh data volumes in its pricing, with hosting costs representing a smaller portion of the overall fee structure.

Each client matter operates in a single-tenant environment with SOC 2-compliant infrastructure and end-to-end encryption, addressing law firm security requirements.

While ChronoTracer currently relies on manual tagging for categorizing events, the company plans to incorporate more AI-driven features based on customer demand. The platform already uses AI for translation, transcription, and data cleanup in its processing pipeline.

Near-term development priorities focus on customer-requested features, such as filtering by time of day to identify after-hours communications or filtering by the presence or not of an attachment.