The News: Fisent Technologies, a provider of Applied GenAI Process Automation solutions, has secured funding from strategic investors, including Pegasystems, Sand Dollar Capital, and prominent entrepreneurs. This funding will fuel the growth of its BizAI product, which serves as a service gateway between an enterprise technology application or system and a generative AI model. It is designed to manage the complexities of integrating AI into existing business processes. The amount and terms of the investment were not disclosed.
You can read the press release at Fisent Technologies’ website.
GenAI Process Automation Solution Provider Fisent Secures Funding
Analyst Insight: Fisent Technologies announced it had secured funding from Pegasystems, Sand Dollar Capital, and other entrepreneurs to help fund the growth of its BizAI product. This service gateway sits between an enterprise technology application or system and a generative AI model and is designed to manage the complexities of integrating AI into existing business processes.
Founded three and a half years ago with roots in financial services, Fisent developed Biz AI to address a critical gap in the market.
Managing Multiple File and Data Types
A significant challenge in utilizing AI models for enterprise applications is the ability to process and understand various content formats. While existing models can handle basic file types such as images and PDFs, the real world involves a broader spectrum of documents and media. To address this, the company has developed a system capable of interpreting over 150 different content types, making it easier for clients to input data without worrying about compatibility issues. This content processing capability is a core component of their platform.
According to Adrian Murray, Founder and CEO of Fisent, BizAI enables end-to-end automation of repetitive business tasks through generative AI foundation models. It can process and prepare hundreds of different types of data, to which a generative AI model can be applied to intelligently discern and act upon the information contained within the data.
For example, suppose customers submit reimbursement receipts to an airline after a canceled flight. In that case, BizAI can intelligently interpret those receipts, categorize expenses, and discern which expenses are associated with the canceled flight, reducing the time employees need to spend on this task, and letting them refocus their efforts on core tasks.
Model Limitations and Optimization
Another hurdle in AI implementation is the limitations imposed by foundation models themselves. Factors such as quota restrictions due to resource constraints and the varying context window sizes of different models can hinder efficient processing. The company has been actively working on solutions to these challenges, such as optimizing resource allocation and developing strategies to utilize model capacities effectively.
Carving Space in an Evolving Market
From SMBs to mid-market organizations to enterprises, businesses are trying to identify ways to harness the power of AI and, in particular, generative AI. Fisent addresses one of the key challenges—how to activate the myriad types of data held within an organization and enable AI models to act upon that data efficiently and cost-effectively.
Fisent’s solution addresses that need by serving as an intermediary between an organization’s data, applications, workflows, and the AI model itself. The company’s core focus is on building out application programming interfaces (APIs) to work with application development and workflow platforms such as Appian and Pegasystems, as well as pre-built SaaS platforms such as Salesforce and ServiceNow. CEO Murray told me during a briefing that a key differentiator is Fisent’s ability to apply generative AI to quickly stand up new use cases, without needing to store the data.
In addition, the company takes a model-agnostic approach to generative AI, noting that the enterprise market is unlikely to coalesce around a single generative AI model provider and instead feature several different types of models based on functionality, use case, and cost.
The company’s core challenges lie around visibility, which Murray believes will come as they continue to close and publicize new deals with Fortune 500 customers, and simply around educating the market on the value of using a third party to handle this type of integration work, instead of trying a DIY approach or hiring a consultant.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
Pegasystems’ ‘Blueprint’ for Fast-Tracking App and Workflow Dev
CEO Insights and Generative AI Adoption Costs for Developers
Market Insight Report: SaaS-Based Generative AI Pricing Trends
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
