US based cloud and AI company Conversica has released brand-specific AI large language models (LLMs) with contextual response generation.  

Conversica’s LLM can generate more niche responses in answer to prompts using retrieval augmented generation (RAG). 

RAG allows LLMs to be trained on a company’s internal data and information, allowing them to be used for more specialised purposes in the workplace. 

Alongside being able to produce responses that are specific to the company using the LLM, RAG also ensures that the LLM will produce more up-to-date and correct responses. RAG can prevent LLMs from hallucinating, which is an error that makes LLMs generate false responses. 

Conversica Chat is trained solely on its customers’ data, which Conversica states could be attractive to businesses in highly regulated industries. 

“Chat solutions have become ubiquitous in today’s digital landscape. Yet, for Fortune 100 enterprises, leveraging generative AI-powered chat technologies has remained a complex challenge,” stated Conversica’s CEO Jim Kaskade.

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By GlobalData

“Conversica Chat offers a client-specific, single-tenant solution that delivers regulatory compliant and seamless GPT experiences resulting in brand-safe conversations for enterprise revenue teams,” added Kaskade.

Research and analysis company GlobalData forecasts that generative AI will be the fastest growing segment of AI technology. 

Generative AI revenues are expected to grow at a CAGR of 80% between 2022 and 2027, amassing a value of $33bn by 2027. 

Generative AI is set to disrupt every industry and throughout 2024 GlobalData expects more and more companies to rollout AI solutions. 

By 2030, the total AI market worldwide will be worth over $909bn.