on the Centre Stage at London Tech Week 2024, Quantexa, the global leader in Decision Intelligence (DI) solutions for the public and private sectors debuted Q Assist, a context aware generative AI technology suite to help organizations augment trusted decision-making across teams of frontline and information workers. The announcement demonstrates progress against the company’s platform innovation roadmap and comes nearly a year after Quantexa detailed a significant investment in the global artificial intelligence (AI) industry and previewed Q Assist as a stand-alone LLM agnostic copilot.
With the new Q Assist Technology Suite, Quantexa customers will be able to operationalize generative AI for transformational gains without significant investment in infrastructure, tooling, and additional skilled resources.
Frontline and information workers can leverage the power of copilots, linked data, Quantexa’s knowledge graph capability, and other Decision Intelligence Platform features to enhance the accuracy and reliability of generative AI models that interact with all data (structured and unstructured), context, and insight across their organization. Combining LLMs with the rich context within Quantexa’s Decision Intelligence Platform enables a better understanding of data, safely grounds responses, increases performance and trust, and ensures teams have the most accurate, up-to-date information in a single place.
Helping Customers Succeed in the Era of AI
HSBC is one of the organizations currently participating in the Lighthouse Program for early adopters. Each organization in the program envisions using Q Assist in several ways, including:
- Streamlining analysis, investigation, and reporting tasks for information and knowledge workers to achieve greater efficiency.
- Reducing the reliance on data science and operations teams for ad-hoc data requests, giving them time to focus on more strategic tasks.
- Empowering customer facing teams with access to enriched data and insights they need to increase revenue and enhance customer experiences.
- Enabling teams across an organization to consistently make trusted decisions that are traceable and accelerate operational process improvement.
BNY Mellon is currently evaluating joining HSBC in Lighthouse effort. Quantexa worked with Lighthouse Program participants to project one-, three-, and five-year benefits from deploying Q Assist within their customer facing, data science, and investigative teams. It found an almost immediate productivity gain across three core areas: time saving and efficiency, new opportunity identification, and increased conversion rates.
HSBC anticipates that democratizing analytics and accelerating processes across these areas could lead to productivity gains within the first year of deployment. The company also expects to free up employee’s time, allowing them to refocus on other strategic tasks.
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David Rice, Global Chief Operating Officer, Commercial Banking at HSBC, said: “This new solution has the potential to enhance the efficiency and accuracy of complex tasks such as anti-money laundering investigations and sales strategies by providing trusted data and contextual analytics. The introduction of contextual analytics and innovation will enable HSBC to concentrate our resources more productively and ultimately help our customers.”
Quantexa estimates that a tier one global financial institution with three levels of defense in financial crime and fraud compliance efforts, generating approximately 15k alerts a month, could realize significant efficiencies and cost savings by deploying the Q Assist Generative AI Technology Suite:
- Over £17M in savings enabled annually by enhancing and automating investigating and reporting processes across financial crime and fraud.
Quantexa’s CTO, Jamie Hutton, said: “Quantexa’s engineering principle of shaping solutions to deliver maximum customer value has allowed our clients to play an integral role in helping to shape the product requirements for Q Assist. Through the company’s Lighthouse Program for early adopters, we have the benefit of working with industry leaders that provide valuable feedback throughout our roadmap process.”
Eric Hirschhorn, Chief Data Officer, BNY Mellon, said: “We are excited to see this continued innovation from Quantexa. Our multi-year collaboration has helped us to break down data silos and unify our data with unprecedented accuracy. The next phase in our innovation efforts will see us exploring the potential of enabling frontline workers across the bank to use Gen AI to act on the data insights confidently and reach new levels of efficiency in the process.”
How the New Q Assist Generative AI Technology Suite Works
Quantexa’s new generative AI technology suite will combine Quantexa’s Decision Intelligence Platform and Generative AI through a new data integration layer, prompt builder, and copilot that accelerates the ability of teams to make critical business decisions.
Q Assist delivers trusted, extensible AI anchored by Quantexa’s Decision Intelligence Platform. This lets non-technical teams benefit from Quantexa’s critical platform capabilities including a connected data foundation, graph analytics, modeling, and scoring to augment and automate decision making. The Q Assist Technology Suite is comprised of three components:
- Q Assist Integration Layer: the nerve center of Q Assist. It is a framework of tools, connectors, and APIs designed to securely link Quantexa’s Decision Intelligence Platform with LLMs and conversational AI systems right out-of-the-box.
- Q Assist Prompt Builder: an extensible prompt management and sharing capability that easily integrates with external prompt engineering tools and frameworks, such as Microsoft’s Azure Prompt Flow, Semantic Kernel or AutoGen, to put the power in the hands of administrators to define and control prompts and responses that are grounded in contextual data generated by Quantexa’s Decision Intelligence Platform.
- Q Assist Copilot: allows users to query large and disparate data via a natural language interface, understand and summarize data, insights, and findings in real-time, and automate research, investigation, and reporting tasks.
Source: GlobeNewsWire
