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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Overview Energy plans to collect sunlight in orbit and send it to Earth, giving Meta early access to a new source of round-the-clock power
Updated
April 29, 2026 3:20 PM
A corona mass ejection erupts from our sun. PHOTO: UNSPLASH
Overview Energy, a startup focused on space-based power systems, has announced a new agreement with Meta to develop a new source of electricity for data centers. The partnership centres on space solar energy, with an orbital demonstration planned for 2028 and commercial power delivery targeted for 2030.
The deal gives Meta early access to as much as 1 gigawatt of future capacity from Overview’s system. That matters because large technology companies are searching for reliable power sources as demand rises from AI computing and data center expansion.
Overview’s idea is straightforward, though the engineering is ambitious. The company plans to place satellites in orbit that collect sunlight continuously in space. That energy would then be sent to existing solar sites on Earth, where it would be converted into electricity.
Unlike ground-based solar farms, which only generate power when the sun is shining locally, a space-based system is designed to extend power generation beyond daylight hours. In theory, this could help solar facilities produce electricity around the clock without using extra land.
"Space solar technology represents a transformative step forward by leveraging existing terrestrial infrastructure to deliver new, uninterrupted energy from orbit. We're excited to partner with Overview Energy to pioneer innovative energy solutions to advance our AI ambitions and infrastructure", said Nat Sahlstrom, VP of Energy and Sustainability, Meta. "This collaboration demonstrates our commitment to innovation – leveraging cutting-edge technology to strengthen America's energy leadership".
For Meta, the agreement is less about a near-term energy fix and more about securing future options. Major data center operators are increasingly competing for electricity as AI systems require more computing power and more cooling capacity. Traditional energy projects can take years to build, making alternative supply models more attractive.
Overview says its system is designed to work with solar projects that already exist. Instead of building entirely new power plants, the company aims to increase output from current sites by adding energy received from orbit.
"Space is becoming part of America's energy infrastructure", said Marc Berte, CEO of Overview Energy. "Our approach to space solar energy enables hyperscalers and technology providers to secure clean power with reliable siting, and speed to power.” "Together with Meta, we're looking beyond traditional constraints on where and when power can be delivered to meet the growing demand for electricity".
The larger significance of the partnership is what it signals about the energy market. As AI infrastructure expands, companies are beginning to look beyond conventional grids, gas plants and land-based renewables. Technologies once considered experimental are now being explored as part of long-term infrastructure planning.
There is still a long road ahead. Space solar power has been discussed for decades, but commercial deployment remains unproven. Launch costs, regulation and system reliability will all matter.
Even so, the Meta-Overview agreement shows how rising demand for constant power is reshaping where the technology sector looks for its next energy source.