Among equity research analysts Hudson Labs (formerly Bedrock AI) has emerged as one of the most respected and commonly used AI tools within the industry, as highlighted in a recent Forbes article. Established in 2019 and formerly known as Bedrock AI, the story of Hudson Labs demonstrates the growing role of specialized AI in finance.
Hudson Labs' development of finance-specific large-language models (LLMs) is augmenting the way traditional equity research has been done. Our technology serves clients with over $600 billion in assets under management at some of the world’s most successful investment firms.
“Hudson Labs' platform enables capital markets professionals to tap the power of industry-tailored AI. Their success spotlights three key AI deployment criteria -- specialization, trustworthiness and compelling job-acceleration appeal.” ~ Noah Barsky, Forbes
With often millions at stake for each individual investment, the importance of accuracy and reliability of tools in investment research cannot be overstated. Hudson Labs addresses this need by tailoring their AI solutions specifically for the financial sector, ensuring accuracy and contextual relevance.
Highlights from the Forbes article by Noah Barsky:
Trust is crucial
As quoted by Forbes, Suhas Pai, Hudson Labs CTO and co-founder, emphasises the importance of contextualizing AI for finance tasks and what makes Hudson Labs approach unique:
“Trust and reliability are crucial for an AI product in the financial domain to succeed. Current LLMs suffer from too many issues, including their poor reasoning abilities, propensity to stray away from being factual, and lack of controllability. Instead of using a single LLM end-to-end, we break down a task — like company background memo generation — into dozens of sub tasks. Each subtask is tackled on its own merits, including by using specialized LLMs. This way, we are able to design and deliver highly reliable products that overcome the common limitations of LLMs that persist.”
Fear of job replacement is real
Hudson Labs CEO and co-founder Kris Bennatti, highlighted:
“When analysts worry about their jobs, I remind them that they have to consume vast amounts of information to develop a differentiated view from the rest of the market. If AI makes the process of consuming that information 50% or even 15% easier, their job remains the same with less friction and frustration. For instance, one of Hudson Labs’ contributions to financial AI research is a proprietary noise suppression technique that can be applied to corporate disclosures, call transcripts, etc. In an AI-driven future, you won’t have to read ten pages of nonsense just to find the single point that matters.”
One-size fits all AI models don’t work at work
In a comparative assessment with other tools and chat bots Hudson Labs' AI demonstrated superior accuracy in financial extraction, while other tools hallucinated and presented plausible-sounding false information. This study highlighted the limitations of generic AI in dealing with specialized, technical data and underscores Hudson Labs' expertise in creating finance specific AI solutions.
Hudson Labs' rebranding from Bedrock AI, as detailed in this press release, symbolizes the company's growth and its commitment to advancing finance-specific AI research. This change reflects our expanded vision and ongoing innovation in the field.
As the next step in company evolution Hudson Labs is introducing new products focused on equity research workflow automation. The new product suite includes earnings transcript summaries, auditable automated investment memos and AI-generated news feeds. These innovations are expected to further enhance the efficiency of financial information processing and analysis, and amplify the impact of top performers in equity markets.
With its focus on specialized, accurate, and reliable AI solutions in finance, the company is redefining the landscape of equity research. If you are interested to learn more or try the product book a demo now and a member of the Hudson Labs team will be in touch with you shortly.
