Quantexa, a global firm focused on decision intelligence solutions for the public and private sectors reveals its Decision Intelligence Platform roadmap, and provides an update on Q Assist, a generative artificial intelligence (AI) assistant that previewed in July last year.
Quantexa also announced a partnership with Microsoft (NASDAQ:MSFT).
Dan Higgins, Quantexa’s Chief Product Officer, was joined by Kate Rosenshine, Global Technology Director, Strategic Partnerships at Microsoft, where they announced the immediate availability “of Quantexa’s Decision Intelligence Platform on Microsoft Azure Marketplace and plans to bring a new cloud-native AI solution to mid-size banks in the United States.”
Quantexa’s plan to lead the decision intelligence category is “anchored in helping enterprises and government agencies use contextual analytics and AI to improve organization-wide decision making.”
Quantexa is putting an emphasis “on practical, real-world applicability today, with an eye on helping customers plan for future technology deployments.”
As part of Quantexa’s growth strategy, the company showcased the platform’s ability “to use AI to build a trusted data foundation and bring greater effectiveness to existing decisioning processes, while seamlessly integrating into customers’ existing technology infrastructure.”
Dan Higgins, Quantexa’s Chief Product Officer, stated:
“When it comes to Quantexa’s technology roadmap, we are guided by our client’s needs and leadership ambition in decision intelligence. This requires us to help our customers break down organizational silos to create a trusted data foundation, automate and augment decision making, and support continuous evaluation and improvement throughout decision processes. With the introduction of new capabilities and solutions, we remain steadfastly focused on delivering groundbreaking innovation that helps organizations protect, optimize, and grow.”
Quantexa Highlights Four Key Roadmap Pillars
Powering human/AI decisioning: Quantexa continues to pioneer solutions and tools to enable the use of multiple data sources and AI “to automate business decision logic across various applications.
Quantexa is updating its platform with enhanced workflow capabilities “including new customizable scoring, alerting, and decisioning models.”
Quantexa debuted the platform’s new case management capabilities and “an early adoption update to Q Assist, which is being deployed by customers in banking, telecommunications, and government agencies, in pilot programs to tackle financial crime, fraud, and risk, and to identify new revenue opportunities with customer intelligence.”
Operationalizing data at scale with AI and contextual analytics: Quantexa’s ability to help customers build “a trusted data foundation and gain single customer views remains a top driver of platform adoption.”
To meet increasing demand and unique industry complexities, Quantexa showcased advancements “in data management, contextual analytics, and AI capabilities.”
Quantexa previewed the ability to “move beyond news intelligence to support the ingestion and analysis of any unstructured data source via entity resolution and give the ability to customers to enable large scale graph analysis and graph machine learning by combining large language models (LLMs) and knowledge graphs.”
Accelerating time-to-value through simplified deployments and packaged solutions: Quantexa announced new options to “make it easier for customers and partners to get up and running with new deployment methods including the introduction of out-of-the box configurations, as well as low-code and no-code tools.”
This year, Quantexa is also investing in “accelerating the enablement of its growing ecosystem of partners, which includes PWC, EY, Dun & Bradstreet, KPMG, and Moody’s, who were presenting partners at QuanCon24.”
Integrating with customers’ existing technology stacks and processes: Quantexa’s Decision Intelligence Platform has “an open and extensible architecture with scalable APIs and streamlined integrations with downstream applications and systems.”
Future efforts will focus on “building a standardized framework and out-of-the-box connectors.”
