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Due diligence is a high-priced line of work , and not just in the kingdom of investing . Even for a company endeavor to establish a new product or research a partnership , finding the correct data point and doing the research can take weeks and get very costly if they are to make an educated decisiveness — particularly when third - party agencies and consultant get involved .
A new AI inauguration calledBridgetown Researchsays it can make a gouge in that cost cornerstone and speed up the process by using AI agents that can do most of the data point collection and research body of work that goes into due diligence . And as part of this effort , the inauguration recently raised $ 19 million in a Series A round carbon monoxide - precede by Accel and Lightspeed .
Co - founded in December 2023 by its CEO Harsh Sahai , a former McKinsey employee and research scientist at Amazon , Bridgetown Research has build three types of AI agents that it claim can get together information , collate and condense that data , and present it in an gentle - to - read format .
Bridgetown is exploit the very networks that consultants and researcher often habituate to cumulate insights : networks of industry expert who can furnish insight on a particular party or sphere . The startup basically partners with these expert connection and then uses its AI voice agent to question experts for the entropy the company require to find for its guest .
“ Because insiders do n’t have to schedule a call with a human being , they can log on whenever and have a conversation , ” Sahai said in an interview . “ Instead of mouth to one fourth-year executive director , you could talk to mid - tenure hoi polloi , but a raft more of them … at a much gamey scale . ”
Bridgetown ’s 2d set of agents then use large nomenclature manikin ( LLMs ) alongside tool for clustering and regression to see the data collected by the voice agents , and pass this information back to the LLM to summarize the answer . Finally , the third set of agents use little language models to reproduce the interpretation in a digestible form , like a presentation .
Using these agent , the inauguration tell it can produce an initial due program analysis in 24 hours with input from hundreds of respondents .
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Sahai sound out clients can either use Bridgetown ’s agents to gather information and insights on their own , or they can hire an independent advisor or a little consulting firm to go with the agents to get the same lineament of analysis as they would from house like McKinsey or Bain .
That sounds likeable , but big language model and the AI agent build on top of them still tend to hallucinate — that is , they tend to make up information . So how is an investor to hope research reproduced by an AI agent ? Sahai say the startup addresses this with its “ steerability and auditability ” approach .
This intend , he explicate , clients can review the data and trace every step the federal agent took to arrive at its ratiocination , standardised to the “ reasoning ” AI models out there . Additionally , the voice agents record their conversations with the experts they interview so that the information can be manually verify .
He add together that the AI agent do not rely on a exclusive information source . Instead , they tuck information from multiple sources , understand it using large language model , and then apply mulct - tuned models to process the data .
“ We have n’t view our approach before , ” Sahai read . “ Most platforms pull up stakes it to you to pull in the information you need , and then they will work on it on your behalf . ”
Bridgetown is n’t the first to tackle this chance to make due program easier — we already have inauguration likeMako AIandDiligentIQin the blank . However , Sahai thinks other political platform do not provide a complete enough solvent .
Bridgetown Research has two customers in the U.K. and a dozen in the U.S. These admit top - tier secret fairness and speculation upper-case letter funds , consulting firms , and great corporation that address the M&A pipeline , Sahai said .
