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
Quantara AI launches a continuous platform designed to estimate the financial impact of cyber risk as companies move beyond periodic assessments
Updated
March 17, 2026 1:02 AM
A person tightrope walking between two cliffs. PHOTO: UNSPLASH
Cyber risk is increasingly treated as a financial issue. Boards want to know how much a cyber incident could cost the company, how it could affect earnings, and whether current security spending is justified.
Yet many organizations still measure cyber risk through periodic reviews. These assessments are often conducted once or twice a year, supported by consultants and spreadsheet models. By the time the report reaches senior leadership, the company’s systems may have changed and new threats may have emerged. The way risk is measured does not always match how quickly it evolves.
This gap is where Quantara AI is positioning its new platform. Quantara AI, a Boise-based cybersecurity startup, has introduced what it describes as the industry’s first persistent AI-powered cyber risk solution. The system is designed to run continuously rather than rely on occasional assessments.
The company’s core argument is straightforward: not every security weakness carries the same financial consequence. Instead of ranking issues only by technical severity, the platform analyzes active threats, identifies which company systems are exposed, and estimates how much money a successful attack could cost. It uses statistical models, including Value at Risk (VaR), to calculate potential losses. It also estimates how specific security improvements could reduce that projected loss.
The timing aligns with a broader market shift. International Data Corporation (IDC) projects that by 2028, 40% of enterprises will adopt AI-based cyber risk quantification platforms. These tools convert security data into financial estimates that can guide budgeting and investment decisions. The forecast reflects growing pressure on security leaders to present risk in terms that boards and regulators understand.
Traditional compliance and risk management systems often focus on meeting regulatory standards. Vulnerability management programs typically score weaknesses based on technical characteristics. Consultant-led risk studies provide detailed analysis, but they are usually performed at set intervals. In fast-changing threat environments, that model can leave decision-makers working with outdated information.
Quantara’s platform attempts to replace that periodic process with continuous measurement. It brings together threat data, internal system information and financial modeling in one system. The goal is to show, at any given time, which specific weaknesses could lead to the largest financial losses.
Cyber risk quantification as a concept is not new. What is changing is the expectation that these calculations be updated regularly and tied directly to financial decision-making. As cyber incidents carry clearer monetary consequences, companies are looking for ways to measure exposure with greater precision.
The broader question is whether enterprises will shift fully toward continuous, AI-driven risk analysis or continue relying on periodic external assessments. What is clear is that cybersecurity discussions are moving closer to financial reporting — and tools that estimate potential loss in dollar terms are becoming central to that shift.