A breakdown of the mission aiming to turn space into the next layer of digital infrastructure.
Updated
January 8, 2026 6:32 PM
The Hubble Space Telescope, one of the fist space infrastructures. PHOTO: UNSPLASH
PowerBank Corporation and Smartlink AI, the company behind Orbit AI, are preparing to send a very different kind of satellite into space. Their upcoming mission, scheduled for December 2025, aims to test what they call the world’s first “Orbital Cloud” — a system that moves parts of today’s digital infrastructure off the ground and into orbit. While satellites already handle GPS, TV signals and weather data, this project tries to do something bigger: turn space itself into a platform for computing, artificial intelligence (AI) and secure blockchain-based digital transactions. In essence, it marks the beginning of space-based cloud computing.
To understand why this matters, it is helpful to examine the limitations of our current systems. As AI tools grow more advanced, they require massive data centers that consume enormous amounts of electricity, especially for cooling. These facilities depend on national power grids, face regulatory constraints and are concentrated in just a few regions. Meanwhile, global connectivity still struggles with inequalities, censorship, congestion and geopolitical bottlenecks. The Orbital Cloud is meant to plug these gaps by building a computing and communication layer above Earth — a solar-powered, space-cooled network in Low Earth Orbit (LEO) that no single nation or company fully controls.
Orbit AI’s approach brings together two new systems. The first, called DeStarlink, is a decentralized satellite network designed for global internet-style connectivity and resilient communication. The second, DeStarAI, is a set of AI-focused in-orbit data centers placed directly on satellites, using space’s naturally cold environment instead of the energy-hungry cooling towers used on Earth. When these two ideas merge, the result is a floating digital layer where information can be transmitted, processed and verified without touching terrestrial infrastructure — a key shift in how AI workloads and cloud computing may be handled in the future.
PowerBank enters the picture by supplying the electricity and temperature-control technology needed to keep these satellites running. In space, sunlight is constant and uninterrupted — no clouds, no storms, no nighttime periods where panels lie idle. PowerBank plans to provide high-efficiency solar arrays and adaptive thermal systems that help the satellites manage heat in orbit. This collaboration marks a shift for PowerBank, which is expanding from traditional solar and battery projects into the realm of digital infrastructure, AI energy systems and next-generation satellite technology.
Describing the ambition behind this move, Dr. Richard Lu, CEO of PowerBank, said: “The next frontier of human innovation isn't just in space exploration, it's in building the infrastructure of tomorrow above the Earth”. He pointed to a future market that could surpass US$700 billion, driven by orbital satellites, AI computing in space, blockchain verification and solar-powered data systems. Integrating solar energy with orbital computing, he said, could help create “a globally sovereign, AI-enabled digital layer in space, which is a system that can help power finance, communications and critical infrastructure”.
Orbit AI’s Co-Founder and CEO, Gus Liu, describes their satellites as deliberately autonomous and intelligent. “Orbit AI is creating the first truly intelligent layer in orbit — satellites that compute, verify and optimize themselves autonomously”, he said, “The Orbital Cloud turns space into a platform for AI, blockchain and global connectivity. By leveraging solar-powered compute payloads and decentralized verification nodes, we are opening an entirely new, potentially US$700+ billion-dollar market opportunity — one that combines energy, data and sovereignty to reshape industries from finance to government and Web3. PowerBank's expertise in advanced solar energy systems will be significant in supporting this initiative."
This vision is not isolated. Earlier this year, Jeff Bezos echoed a similar idea at Italian Tech Week, saying: “We will be able to beat the cost of terrestrial data centres in space in the next couple of decades. These giant training clusters will be better built in space, because we have solar power there, 24/7 — no clouds, no rain, no weather. The next step is going to be data centres and then other kinds of manufacturing.” His comments reflect a growing industry belief that space-based data centers will eventually outperform those on Earth.
The idea gains traction because the advantages are practical. Space offers free, constant solar power. It provides natural cooling, which is one of the costliest parts of running data centers on Earth. And above all, satellites in low-Earth orbit operate beyond national firewalls and political boundaries, making them more resilient to outages, censorship and conflict. For industries that rely heavily on secure connectivity and real-time data — finance, defense, AI, blockchain networks and global cloud providers — this could become an important alternative layer of infrastructure.
The upcoming Genesis-1 satellite is designed as a demonstration mission. It will test an Ethereum wallet, run a blockchain verification node and perform simple AI tasks in orbit. If the technology works as expected, Orbit AI plans to add several more satellites in 2026, expand into larger networks by 2027 and 2028 and begin full commercial operations by the decade’s end.
To build this system, Orbit AI plans to source technologies from some of the world’s most influential players: NVIDIA for AI processors, the Ethereum Foundation for blockchain tools, Galaxy Space and SparkX Satellite for satellite components, Galactic Energy for launch systems and AscendX Aerospace for advanced materials.
If successful, the Orbital Cloud could become the first step toward a world where part of humanity’s data, computing power and digital services run not in massive buildings on Earth, but in clusters of autonomous satellites illuminated by constant sunlight. For now, the journey begins with a single launch — a test satellite aiming to show that space can do far more than connect us. It may soon help power the systems that run our economies, technologies and global communication networks.
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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.