Fisent Technologies is First to Offer Applied Generative AI Process Automation Solution with Full Model Optionality
Leader in Applied GenAI Process Automation Solutions Ensures the Ability to Easily Select, Combine, and Move Between All Types of GenAI Models
Fisent Technologies today announced it is the first to deliver an Applied GenAI Process Automation solution that offers full model optionality. The Fisent BizAI solution allows enterprises to select the right LLMs for the processes they are looking to automate and to effortlessly shift processes to different models, adjusting for variables such as content, structure, size, and data latency.
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Generative AI models continue to advance at a rapid pace and new LLMs are being introduced by well-funded market challengers at almost the same velocity. In a recent CB Insights survey of enterprise customers using LLMs, 34% of enterprises report currently using at least two LLM developers, 41% are using three, and 22% report using four or more LLM developers. This has created an urgent need for systems that can seamlessly add and shift the GenAI models best suited to the specific use case requirements.
Fisent BizAI capabilities essential to model optionality include:
- Support initial model selection based on use case fit
- Facilitate seamless switching between models if better options emerge or as initial choices evolve
- Offer flexibility in host selection and management for both Foundational models (when available) and proprietary LLMs
- Enable the models to process any content source/type
- Integrate seamlessly with any application/business process management (BPM) layer
Optionality Use Cases
“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,” explains 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.”
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The following real-world BizAI use cases underscore how certain LLMs are more appropriate than others depending on cost, structure, latency, and other factors.
- For a health insurance company seeking to process highly varied invoices received from providers, BizAI can be utilized to analyze content, such as the associated care notes, and expedite the overall review process. The complexity of this process and the requirement for high accuracy necessitates a state-of-the art LLM like GPT4o.
- For an enterprise looking to streamline its credit dispute process across millions of transactions, BizAI could be used to classify the supporting evidence, significantly reducing the time to adjudication. Given the high volume of content, a more cost-efficient and lightweight model like Llama 3.1 would be employed.
Fisent’s BizAI enables end-to-end automation of repetitive business tasks by leveraging the power of Foundational GenAI models. Fisent has helped harness transformative GenAI models for enterprises from small banks to Fortune 500 corporations, transforming processes that currently require intensive human interpretation of content.
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