As workplace knowledge spreads across chats, AI firms are building systems that can structure, retrieve and preserve it over time.
Updated
May 11, 2026 5:24 PM
A messaging app on a phone. PHOTO: ADOBE STOCK
Votee AI, an enterprise AI company headquartered in Hong Kong, has partnered with its Toronto-based research lab Beever AI to launch Beever Atlas. The new platform is designed to turn workplace chats into searchable knowledge that AI systems can retrieve and understand.
The release focuses on a growing issue inside organisations. Much of today’s workplace knowledge now exists inside chat platforms such as Slack, Microsoft Teams, Discord and Telegram. Important discussions, project decisions and technical information often disappear into long message histories that are difficult to search later.
Beever AI developed the platform to organise those conversations into a structured system for AI assistants. The software connects with Telegram, Discord, Mattermost, Microsoft Teams and Slack, then converts conversations into linked records of people, projects, files and decisions.
The collaboration combines Votee AI’s enterprise infrastructure work with Beever AI’s research around AI memory systems. The companies are releasing two versions of the product. The open-source edition is aimed at individual developers, researchers and creators. The enterprise edition is designed for banks, government agencies and larger organisations with stricter security requirements.
The release also reflects a broader shift happening across the AI industry. Companies are increasingly looking at how AI systems store and retrieve long-term knowledge, rather than relying solely on large context windows or search-based retrieval.
Earlier this year, OpenAI founding member and former director of AI at Tesla Andrej Karpathy discussed the growing need for what he described as “LLM Knowledge Bases.” He argued that AI systems need structured and evolving memory rather than depending only on context windows and vector search.
Beever Atlas approaches that problem through workplace communication. Instead of focusing mainly on uploaded files, the system is designed around conversations that happen daily across team chat platforms. It can also process images, PDFs, voice notes and video files within the same searchable system.
The companies say the software is designed to work directly with AI assistants and coding tools such as Cursor, AWS Kiro and Qwen Code. Integrations for OpenClaw and Hermes Agent are expected later in 2026.
Pak-Sun Ting, Co-Founder and CEO of Votee AI said: "Hong Kong has always been known for property and finance. Beever Atlas is proof that world-class AI infrastructure can emerge from an HK-headquartered company and be shared openly with the world. Every growing organization faces the same silent liability: conversational knowledge loss. Beever Atlas turns this perishable resource into a compounding organizational asset."
A large part of the enterprise version focuses on privacy and access control. The system mirrors permissions from Slack and Microsoft Teams so users can only retrieve information they are already authorised to access. Permission updates are reflected automatically when access changes inside company systems.
The enterprise edition also includes audit logs, encryption controls and data retention settings for organisations handling sensitive internal data. Companies can run the software entirely inside their own infrastructure using Docker and connect it to their preferred AI models through LiteLLM.
The companies argue that organising information is more useful than simply storing chat archives. Jacky Chan Co-Founder and CTO of Votee AI said: "The key technical decision was to treat agent memory as a knowledge engineering problem, not a retrieval problem. Structure beats similarity — a typed graph of who works on what is more useful to an AI than vector search over a Slack archive."
The software also includes protections against prompt injection attacks and systems designed to reduce hallucinated responses. According to the companies, the AI is designed to return “I don't know” with citations when confidence is low instead of generating unsupported answers.
As workplace communication becomes increasingly fragmented across chat platforms, companies are beginning to treat internal conversations as information that AI systems can organise, retrieve and build on. Beever Atlas reflects a broader push to turn everyday workplace communication into long-term organisational memory.
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A Hong Kong pilot explores how creator-led distribution could reshape livestreaming for global competitions
Updated
May 1, 2026 2:25 PM
A dance crew performs in sync on stage at World of Dance under spotlights. PHOTO: WORLD OF DANCE HONG KONG
On January 22, 2026, World of Dance Hong Kong became the first global event to pilot Mitico’s community-based livestreaming model. The idea is simple: rethink how live competitions are shared in a digital-first world.
Instead of relying on a single official broadcast, the event was produced as one centralised live feed. It was then distributed across multiple creators and influencers, each hosting the stream for their own audience.
This gave creators room to add their own commentary, adapt the language and bring in cultural context that suited their communities, while the production remained consistent behind the scenes.
“Dance is a universal language”, said David Gonzalez, President of World of Dance. “Our collaboration with Mitico to produce an international, creator-led livestream in Hong Kong allowed a regional competition to reach a global audience. With personalised commentary from hosts in different languages, we can begin to see how regional events may connect through global communities”. This approach points to a shift away from traditional broadcaster-led distribution and toward creator-led amplification.
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Mitico’s approach begins with a familiar industry challenge: the high cost of production and licensing, which often makes it difficult to livestream cultural and sports events at scale.
“Many cultural and sports competitions are never livestreamed because traditional broadcasting is too costly and complex”, said Chengcheng Li, Founder of Mitico. “By distributing a centralised production feed through creators and community hosts, regional events can reach global audiences while maintaining a unified production workflow”.
World of Dance (WOD) offered a natural test environment. It started as a global dance competition platform before entering a television partnership with NBC, which later produced four seasons of the World of Dance reality series. While the television programme concluded in 2021, the competition business has continued to expand through an international network of partners. Today, World of Dance competitions are represented in more than 72 countries, producing nearly 100 events each year, with a digital audience of more than 34 million followers across platforms
Despite that scale, many competitions are not livestreamed due to the high production costs and technical demands associated with traditional broadcasting. The Hong Kong event was selected to assess whether a community-led distribution model could offer a more scalable alternative for live coverage.
While no changes to World of Dance’s broader distribution strategy have been announced, the Hong Kong pilot offers an early indication of how global competitions may rethink livestreaming in an increasingly creator-driven media environment.