ByteGenie links hotels with travelers using AI

Hotels can save 85% of their time while looking for occupants.

ByteGenie Pte Ltd. seeks to raise $837,000 (US$650,000) to help more sales teams in the hospitality sector connect with companies and business travelers using artificial intelligence (AI).

The Singapore startup had raised $515,000 (US$400,000) as of early June, Jiale Tan, co-founder and CEO at ByteGenie, told Singapore Business Review.

“We help corporate sales teams generate leads in real time, saving them 85% of time back for closing deals,” she said via Zoom, citing feedback from a large hotel chain client. “Our AI agent can do the work of the entire data team.”

The number of qualified leads for the hotel chain also grew 10 times, she pointed out.

“Before, sales representatives would spend an entire week manually researching events, exhibitors, and potential customers to sell hotel rooms and venue spaces to, often ending up with only around 30 qualified leads,” Tan said.

“With ByteGenie, they can now get over 300 highly qualified leads, along with strong intent signals like what kind of events are happening, who the exhibitors are, and what specific information those exhibitors are engaging with,” she added.

About 60% to 70% of hotel sales are driven by travelers attending meetings, incentives, conferences, and exhibitions (MICE), according to Tan.

“These events are very valuable leads for corporate sales teams because they sell hotel rooms, conference spaces, exhibition booth spaces, and meeting rooms,” she said.

Gathering buyer data based on custom sales criteria, however, is very challenging and takes thousands of manual hours, she pointed out.

“Our AI agent eliminates that manual work. Teams can simply instruct our AI, go for lunch or coffee, and return to complete datasets,” she added.

ByteGenie also prides itself on accuracy. Majid Hasan, chief technology officer at the company, said the startup is built on a Graph AI Agent architecture instead of large language models (LLM) like ChatGPT and Gemini.

Graph AI Agents are built to follow logic like a flowchart, while LLMs try to guess answers based on language patterns, which can lead to mistakes.

LLMs are like a black box, Hasan said. “There is never a guarantee that it matches the user's criteria, especially in use cases where the user needs to execute an exact business logic.”

For example, a marketing team must have very detailed sets of rules or criteria when trying to determine which customers are eligible for which type of rewards based on the purchases they have made. “Doing that with LLMs is virtually impossible—there would be so many errors.”

ByteGenie plans to invest more in its AI tools and expand automation once it gets more funding. It aims to boost revenue five times and serve 20 enterprise customers by year-end.

The company’s annualised revenue has reached six figures, generated from nine contracts with seven enterprise clients.