Six technology companies showcased solutions for financial research, wealth management, consumer insight and security to investors and institutions.
Updated
November 14, 2026 11:54 PM
.jpg)
Arnold Lau and King Leung (back row, fourth and fifth from left), Associate Directors-General of Investment Promotion at InvestHK, join the Ventureport team and representatives from the six technology companies. PHOTO: VENTUREPORT
Ventureport hosted the soft launch of InvestHK’s Fast-Track Connect at its AI+ Tech+ Finance+ gathering on 30 October, bringing more than 100 guests to Pier 1929 in Wan Chai.
Sponsored by InvestHK, the event brought investors, institutional representatives and technology companies together to explore investment and business partnerships. Six companies took the stage to showcase software solutions for financial professionals, consumer research, local AI computing and digital asset security.
.jpg)
The Acting Head of Startups, at InvestHK, Chin-yung (CY), and the Senior Vice President (Fintech), Pauline Fan, introduced Fast-Track Connect. They explained how the agency’s international network connects it with technology companies seeking investment, customers and business opportunities in Hong Kong.
.jpg)
Their remarks also highlight the need for a more structured approach to build these connections. Investors need easier ways to identify companies that match their interests, while institutions seeking new technology need access to businesses whose products could support their operations or benefit their customers.
To address this need, Fast-Track Connect provides an online platform where technology companies can publish profiles outlining their products and funding needs. Investors and corporate participants can identify relevant businesses and contact them to explore potential investments or collaborations. Service providers and community partners are also part of the platform. Alongside investors and corporate participants, these groups are designated as Champions on the platform.
Curated by InvestHK and supported by the Financial Services and the Treasury Bureau, Fast-Track Connect builds on the Global Fast Track Programme. It aims to help local enterprises expand into Chinese Mainland, Southeast Asia and other markets.
.jpg)
AlphaPai, an AI-powered investment research platform developed by financial technology company RabyteTech, presented tools for financial research, including gathering data, monitoring financial instruments and comparing information from corporate earnings calls.
.jpg)
At the event, the team explained how users can give research instructions in everyday language, while the software retrieves and processes information to prepare reports and presentation materials. Examples included tracking market developments and comparing company statements over time. The team also emphasised the importance of traceable sources, allowing analysts to verify the information behind their research.
A2B2.AI, a fintech startup, presented AI- powered tools designed to support investors and wealth advisers. Its specialist AI agents—software designed to carry out particular tasks—help prepare client meeting briefings, monitor financial products approaching maturity and identify market developments relevant to individual clients, according to the team.
.jpg)
For investors, the tool can help make sense of lengthy documents provided by advisers and bring information from different accounts together to assess risk exposure. For wealth professionals, the tools support preparation and follow-up around client meetings.
The team described its approach as combining AI with human expertise to support financial decision- making. It also clarified that the platform does not execute investment transactions on behalf of clients, leaving those decisions and actions in their hands.
Preferences AI, an AI startup specialising in synthetic consumer research, presented simulated consumer profiles that businesses can use to explore how different audiences might respond to products, pricing and marketing messages. These profiles generate modelled responses rather than feedback from people directly interviewed or surveyed.
.jpg)
The company described that its profiles are grounded in population data and account for differences between local audiences Businesses can use them to explore pricing or packaging options, as well as ask follow-up questions to understand the reasons behind a particular response. The team also discussed testing its models and working with academics to help validate the approach. It said the technology could help businesses explore consumer preferences more quickly.
ByteFuture, an AI infrastructure startup, focused on running AI on users’ own hardware. It introduced Olares, its operating system, and Olares One, a device designed to run AI models and applications locally.
.jpg)
Its applications included personal assistance, financial research and content creation. The team argued that users handling private documents or proprietary trading strategies may prefer to retain that material on equipment they control.
A demonstration of AI-generated video illustrated creative work the team said could run locally. It also described applications and agents available through its software marketplace.
PureGlobal, a fintech company, addressed digital asset custody: the systems used to safeguard access to digital assets. Its team described technology for protecting access credentials and supporting offline transactions without a conventional internet connection.
.jpg)
The presentation focused on infrastructure for institutions holding and transferring digital assets, including security under different operating conditions.
SlowMist, a blockchain security firm, examined the risks of giving AI agents permission to read information and perform tasks. Its examples included malicious instructions concealed in material an agent might encounter and attacks exploiting access granted to software.
.jpg)
The team discussed security auditing, monitoring and investigations alongside risks arising from third-party tools and an agent’s stored information. One scenario involved exposing a wallet’s recovery phrase, which can give someone control over its assets.
Keep Reading
A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
August 10, 2026 5:56 PM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.