人工智能方案目錄

Agentic PRISMA is ClusterTech’s award-winning enterprise AI Agent platform, designed to overcome the scale, multilingual complexity, and security limitations of traditional data tools. Powered by our leading HK-style AI Language Platform and cutting-edge AI technologies—including large language models (LLMs), agentic workflow automation, and Retrieval-Augmented Generation (RAG)—Agentic PRISMA connects and analyzes information from news, social media, and internal enterprise systems, delivering secure, customizable, and actionable intelligence that turns fragmented data into a strategic asset. The platform has been successfully deployed across finance, government, and other sectors, offering tailored social listening, risk assessment, and specialized services such as custom LLM deployment and bespoke system development—helping financial institutions maintain compliance, mitigate risks, uncover hidden opportunities, and make data-driven decisions.

1. Cybercrime Investigation System for Public Sector: The solution automates extraction from non-standard bank documents, cutting manual work and digitising records with OCR. A centralised system unifies databases for a single officer view, while a dashboard visualises maps, case severity, and suspect links, improving resource allocation.

Benefits include faster processing and investigations, fewer errors, better fraud detection and compliance, improved public safety, and scalability. Success requires phased rollout, strong data governance, privacy safeguards, and bank interoperability. Costs include software, infrastructure, integration, compliance, training, maintenance, and change management.

2. Text Analytics on News Articles for a financial regulator : The solution improves public services by automating global financial news monitoring and giving early warnings on critical risks. Optimised queries extract relevant banking articles, the PRISMA Text Analytics Engine classifies topics and risk levels, and a web portal tracks global trends of topics and entities. LLM enhancement discovers new entities, improving coverage over time.

Benefits include faster risk detection, more proactive supervision, better resource allocation, broader coverage, and stronger regulatory decisions that support financial stability, market integrity, and investor protection. Success requires strong data governance, human oversight, and phased rollout. Costs include data licensing, PRISMA and LLM development, integration, infrastructure, compliance, training, and maintenance, plus managing false positives and validating AI outputs.

3. Company Background Search for Financial Institute: the solution improves services by automating the collection and integration of news and company data from diverse sources, especially mainstream search engines, cutting the time spent on manual research and background cross-checking. PRISMA NLP and RAG functions analyse news intelligently, automatically identify the industry category, display webpage sources, alert staff when company information differs from declared information, and flag negative news. This speeds up KYC, AML, credit assessment, onboarding, and ongoing monitoring, enabling faster and more accurate decisions, better customer experience, and stronger protection against fraud and risky counterparties.

Benefits include significant time savings, fewer manual errors, consistent and auditable due diligence, early risk alerts, stronger regulatory compliance, improved decision-making, and scalability across large volumes of companies. Overall value depends on data quality, human oversight, and a phased rollout. Costs include data access and licensing, system integration, PRISMA and RAG deployment, cloud or on-premise infrastructure, cybersecurity and PDPO compliance, staff training, and ongoing maintenance, plus effort to manage false positives and validate AI outputs.

4. Social Analytics Investigating Drug Abuse Trend for a NGO: PRISMA analyses social media posts on drug abuse from 2016–2020, extracting meaningful context and revealing online trends, emerging drugs, slang, and at-risk groups that case studies miss. Continuous monitoring provides early warnings and supports prevention, outreach, counselling, and policy advocacy.

Benefits include earlier trend detection, better targeting of hidden communities, stronger evidence for policy and funding, and scalability. Value depends on robust data governance, ethical safeguards, and human oversight. Costs include data crawling, PDPO compliance, storage, PRISMA licensing, NLP expertise, training, and maintenance, plus ethical risks like false positives and bias.