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Data Center News > Blog > AI > How Yelp reviewed competing LLMs for correctness, relevance and tone to develop its user-friendly AI assistant
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How Yelp reviewed competing LLMs for correctness, relevance and tone to develop its user-friendly AI assistant

Last updated: March 8, 2025 4:04 am
Published March 8, 2025
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How Yelp reviewed competing LLMs for correctness, relevance and tone to develop its user-friendly AI assistant
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The assessment app Yelp has supplied useful data to diners and different shoppers for many years. It had experimented with machine studying since its early years. Through the current explosion in AI know-how, it was nonetheless encountering hindrances because it labored to make use of trendy massive language fashions to energy some options. 

Yelp realized that prospects, particularly those that solely often used the app, had hassle connecting with its AI options, resembling its AI-powered assistant. 

“One of many apparent classes that we noticed is that it’s very straightforward to construct one thing that appears cool, however very exhausting to construct one thing that appears cool and may be very helpful,” Craig Saldanha, chief product officer at Yelp, instructed VentureBeat in an interview.

It definitely wasn’t all straightforward. After it launched Yelp Assistant, its AI-powered service search assistant, in April 2024 to a broader swathe of consumers, Yelp noticed utilization figures for its AI instruments truly starting to say no. 

“The one which took us without warning was once we launched this as a beta to shoppers — a couple of customers and folk who’re very accustomed to the app — [and they] liked it. We bought such a robust sign that this may achieve success, after which we rolled it out to everybody, [and] the efficiency simply fell off,” Saldanha stated. “It took us a very long time to determine why.”

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It turned out that Yelp’s extra informal customers, those that often visited the positioning or app to discover a new tailor or plumber, didn’t anticipate to be be instantly speaking with an AI consultant. 

From easy to extra concerned AI options

Most individuals know Yelp as an internet site and app to search for restaurant critiques and menu photographs. I exploit Yelp to search out footage of meals in new eateries and to see if others share my emotions a few notably bland dish. It’s additionally a spot that tells me if a espresso store I plan to make use of as a workspace for the day has WiFi, plugs and seating, a rarity in Manhattan.

Saldanha recalled that Yelp had been investing in AI “for the higher a part of a decade.”

“Method again when, I’d say within the 2013-2014 timeline, we had been in a really completely different technology of AI, so our focus was on constructing our personal fashions to do issues like question understanding. A part of the job of creating a significant connection helps folks refine their very own search intent,” he stated.

However as AI continued to evolve, so did Yelp’s wants. It invested in AI to acknowledge meals in footage submitted by customers to establish standard dishes, after which it launched new methods to hook up with tradespeople and providers and assist information customers’ searches on the platform. 

Yelp Assistant helps Yelp customers discover the best “Professional” to work with. Individuals can faucet the chatbox and both use the prompts or kind out the duty they want executed. The assistant then asks follow-up inquiries to slim down potential service suppliers earlier than drafting a message to Professionals who would possibly wish to bid for the job.

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Saldanha stated Professionals are inspired to reply to customers themselves, although he acknowledges that bigger manufacturers usually have name facilities that deal with messages generated by Yelp’s AI Assistant. 

Along with Yelp Assistant, Yelp launched Assessment Insights and Highlights. LLMs analyze consumer and reviewer sentiment, which Yelp collects into sentiment scores. Yelp makes use of an in depth GPT-4o immediate to generate a dataset for an inventory of subjects. Then, it’s fine-tuned with a GPT-4o-mini mannequin. 

The assessment highlights function, which presents data from critiques, additionally makes use of an LLM immediate to generate a dataset. Nevertheless, it’s primarily based on GPT-4, with fine-tuning from GPT-3.5 Turbo. Yelp stated it would replace the function with GPT-4o and o1. 

Yelp joined many different corporations utilizing LLMs to enhance the usefulness of critiques by including higher search capabilities primarily based on buyer feedback. For instance, Amazon launched Rufus, an AI-powered assistant that helps folks discover really useful gadgets.

Massive fashions and efficiency wants

For a lot of of its new AI options, together with the AI assistant, Yelp turned to OpenAI’s GPT-4o and different fashions, however Saldanha famous that irrespective of the mannequin, Yelp’s information is the key sauce for its assistants. Yelp didn’t wish to lock itself into one mannequin and saved an open thoughts about which LLMs would offer the perfect service for its prospects. 

“We use fashions from OpenAI, Anthropic and different fashions on AWS Bedrock,” Saldanha stated. 

Saldanha defined that Yelp created a rubric to check the efficiency of fashions in correctness, relevance, consciousness, buyer security and compliance. He stated that “it ‘s actually the highest finish fashions” that carried out finest. The corporate runs a small pilot with every mannequin earlier than taking into consideration iteration price and response latency. 

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Educating customers

Yelp additionally launched into a concerted effort to teach each informal and energy customers to get snug with the brand new AI options. Saldanha stated one of many first issues they realized, particularly with the AI assistant, is that the tone needed to really feel human. It couldn’t reply too quick or too slowly; it couldn’t be overly encouraging or too brusque.

“We put a bunch of effort into serving to folks really feel snug, particularly with that first response. It took us virtually 4 months to get this second piece proper. And as quickly as we did, it was very apparent and you may see that hockey stick in engagement,” Saldanha stated. 

A part of that course of concerned coaching the Yelp Assistant to make use of sure phrases and to sound optimistic. In spite of everything that fine-tuning, Saldanha stated they’re lastly seeing larger utilization numbers for Yelp’s AI options. 


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TAGGED: assistant, competing, correctness, develop, LLMs, relevance, reviewed, tone, userfriendly, Yelp
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