Fisent Technologies’ BizAI empowers seamless GenAI model switching for end-to-end automations

Fisent Technologies, the company revolutionizing how business is performed by enabling the utilization of generative AI (GenAI) models for the automation of common business processes, is announcing the launch of its Applied GenAI Process Automation solution, BizAI, which empowers enterprises to choose the large language models (LLM) that best fit their unique processes. BizAI offers full model optionality, allowing users to seamlessly add and shift GenAI models as needed.

There is no doubt the rapid evolution of GenAI is a difficult space for enterprises to navigate. By the time a specific GenAI model is implemented, a newer, better model will likely be made available.

BizAI is fundamentally made to address this fluctuating arena of GenAI, facilitating the seamless switch between models as better options emerge or initial choices are revised. These models can process any content source or type, as well as easily integrate with any application or business process management (BPM) layer. With end-to-end automation of repetitive business tasks, BizAI empowers organizations to leverage the power of foundational GenAI models, according to Fisent.

“Different AI models are designed and trained for specific tasks based on their architecture, capabilities, and the nature of the data with which they were trained,” explained Adrian Murray, founder and CEO of Fisent. “Where Gemini excels at audio transcription relative to other models, GPT has an advantage over others for text-based analysis, and the LLMs developed on internal data bring proprietary intelligence to the fold. BizAI allows all of these options to be harnessed to automate and optimize processes.”

There are a variety of use cases where BizAI excels, adjusting for nuance where certain LLMs better suit the cost, structure, and latency demands of an enterprise compared to other models. This includes health insurance sectors, where BizAI can analyze content while adhering to accuracy needs and accommodating complexities; as well as credit dispute needs for evidence classification without incurring high, heavyweight costs.

To learn more about BizAI, please visit https://fisent.com/.