AARchive / After-Action Archive
The Computer Vision platform that converts raw sports video into searchable team assets.
Match footage. Training sessions. Scouting archives.
01 / THE PROBLEM
Every season adds matches, training sessions, and scouting footage. Across years, teams, and platforms, the archive grows. Finding the right moment still depends on someone remembering where to look.
Explore what gets in the way
Valuable video is scattered across folders, seasons, and systems. The bigger the archive, the harder it becomes to navigate.
Knowing which season or folder to open can become a prerequisite for finding an answer.
Coaches and analysts search tags and rewatch recordings to find one player, pattern, or moment.
A single question can mean opening multiple videos and piecing together the relevant evidence by hand.
Evidence behind past performances and tactical decisions becomes difficult to recover as seasons and staff change.
The footage may still be there, while the context behind a previous review lives in someone’s memory.
02 / THE SOLUTION
Ask questions in plain language and find the relevant evidence in your footage. AARchive connects answers to timestamped moments, so your team can return to the source and understand the context.
Working platform foundation
01 / THE QUESTION
Ask about a moment, a pattern, or a situation in your footage. AARchive is being built to connect your team’s questions to relevant moments in its analyzed archive.
Example question“Where did we lose possession under pressure?”
02 / THE SOURCE
Return to the source video at the relevant timestamp. Watch what happened before and after the moment, then use your team’s expertise to interpret it.
The original footage stays central to the review.
03 / THE EVIDENCE
Timestamped references make it possible to check the evidence behind an answer. Review the moments, question the interpretation, and retain useful context for the next review.
Your team can review, correct, and build on what it learns.
Product concept illustration. Hover, focus, or select a step to explore the intended workflow.
Start with the sports video your organization already owns.
Find players, moments, and patterns in natural language.
Review timestamped moments linked to the source video.
03 / CORE CAPABILITIES
Built around the questions that coaches, analysts, and scouts bring to their footage.
Bring match footage, training sessions, scouting clips, and historical archives into one searchable body of team knowledge.
Matches · Training · Scouting · ArchivesMatch footage, training sessions, scouting clips, and historical recordings form the archive. As videos are analyzed and retained, relevant moments become easier to retrieve together.
A question can begin with what happened, rather than where a file was saved.
Describe what you want to find in your own words. Explore players, patterns, and moments without having to remember a file name.
Questions in your team’s languageUse everyday language to explore the footage. Follow-up questions can help a reviewer examine an answer and return to its supporting moments.
Start with a situation your team wants to understand, then use the footage to go deeper.
Connect answers to timestamped clips and moments in the original footage. Review the evidence with its surrounding context.
Answers linked to source footageA useful answer includes a route back to the source: the video and the relevant timestamp. The reviewer can check what is visible and consider the surrounding context.
Coaches and analysts remain responsible for interpreting the evidence.
Keep analysis and questions connected to your archive, helping your organization retain what it learns as people and seasons change.
Knowledge that stays with the teamKeep questions, analysis, and review history connected to the archive. Corrections and retained context help the next person understand what the team learned.
A new season or a change in staff should not mean starting from scratch.
04 / WHO IT’S FOR
AARchive is being built for sports organizations and the people responsible for their video knowledge.
ACROSS SPORTS. ACROSS SEASONS.Find the footage behind tactical patterns, preparation, and performance review.
Find relevant scouting footage and revisit the evidence behind evaluations across seasons.
Make years of sports footage easier to search and organizational knowledge easier to preserve.
05 / ABOUT THE TEAM
Engineering experience spanning computer vision, natural language processing, AI systems, and automation.
CO-FOUNDER & CEO
Computer Vision Engineer
Marie-Chantal has architected NLP systems for Wall Street and engineered computer vision architectures with a focus on bias mitigation across diverse real-world datasets.
Connect on LinkedIn (opens in a new tab)
CO-FOUNDER & CTO
AI Systems Engineer
Leslie brings experience in LLM-driven applications, automated transit infrastructure, and AI integration in safety-critical automation and software systems at Siemens Mobility.
Connect on LinkedIn (opens in a new tab)06 / CONTACT
For teams, partners, and investors interested in what we’re building, we’d welcome a conversation.
Get in touch through LinkedIn.