How Alfa differs from market LLMs

Alfa differs from other market LLMs in several ways. Keep reading to learn how.

The team behind Alfa has been training LLMs for 7 years

Alfa is built considering the following:

  • Deep domain expertise: Our team has several years experience training AI and LLMs which has given us a deep understanding of challenges, terms, regulations, and concepts in the financial industry. This helps give Alfa highly accurate responses and insights.
  • Proprietary financial data integration: Alfa is able to incorporate specialized financial data sources that are unique to Boosted.ai. This ensures that our models generate insights based on reliable and exclusive data.
  • Advanced customization: Alfa caters to diverse client needs—such as institutional investors, advisors, or analysts—with tailored solutions for portfolio management, risk assessment, and trend identification. This results in a system designed to be customized for a wide range of needs.
  • Established trust and reliability: Our partnerships with top financial institutions and a strong track record of delivering advanced insights into events, accelerating stock research and improving portfolio management. This means faster investment decisions and better risk management.

AI Scaling

Traditional market LLMs have a limited ability to read a high volume of words due to static compute. Alfa, on the other hand, is able to read millions of words of text on demand and in real time.

  • Alfa gives a complete summary of all available information due to its ability to process information in real time, ensuring you’re not missing anything.
  • Other market LLMs limit their sources when generating an output to save time and money, not guaranteeing that it won’t miss something.

Constant monitoring

Traditional market LLMs only offer one-time outputs. Alfa, on the other hand, constantly monitors all available datasets to complete ongoing updates to its output. 

  • Alfa’s analysts continuously monitors and updates their output, notifying you of important changes.
  • Alfa’s continuous monitoring keeps information consistent as the workflow used to generate the output remains the same .
  • Other market LLMs only offer one-time outputs, and asking it to update the output would result in inconsistencies as it would not re-run the query in the exact same way.

Finance-specific datasets

Traditional market LLMs are only capable of accessing publicly available datasets. Alfa, on the other hand, has the ability to access exclusive financial datasets on top of those that are publically available.

  • Alfa gives you an enhanced output, ensuring to reference finance-specific sources.
  • Other market LLMs are restricted to publicly available data, meaning they do not have access to all the relevant information needed to create an informed output.

Industry-leading hallucination rates

Traditional market LLMs have an average hallucination rate of 3%. Alfa, on the other hand, is able to ensure lower hallucination rates.

  • Alfa uses multi-article to one fact validation to ensure output is fact-checked correctly.
  • Alfa also provides in-text citations to ensure you can see where each piece of information comes from.
  • Other market LLMs only need a single source to say something for it to be considered factual and do not provide the same amount of detail for in-text-citations.

Read more on how we’re mitigating hallucinations.

Custom data uploads

Traditional market LLMs are trained on the contents of uploaded custom documents. Alfa, on the other hand, enables you to securly upload custom data for analysis.

  • Alfa lets you integrate custom documentation into your analysis for an entirely personalized output.
  • Alfa protects your private information by ensuring that your documentation isn’t shared with anyone.
  • Alfa is never trained on the contents of your documents.
  • Other market LLMs do not keep your uploaded information private and will use uploaded information for training.

Output examples


Prompt


Output

ChatGPT
Output

Why Alfa’s output is better

Compare Construction Partners with its biggest competitors by evaluating market share, revenue growth, profitability, and recent strategic moves. Provide a summary of each competitor’s strengths and weaknesses relative to Construction Partners, and suggest items to monitor in Construction Partners' next earnings call

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Alfa's answer was more detailed and broke down the analysis by field (Profitability, Market Share, Revenue Growth, etc.) while also giving a longer list of competitors. This is likely due to the volume of data sources Alfa can draw from.

Draft a due diligence agenda for Thomson Reuters based on your assessment of all the internal documents we have. Focus on financial performance, management team background, recent strategic initiatives, and competitive positioning. Summarize key points under each category and suggest specific questions for the management team.

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ChatGPT only gives a framework for items to analyze to perform a due diligence agenda. Alfa provided more value by pulling numbers, news, and a brief analysis of the news.

Give me a list of the top 10 companies in the S&P 500 by most recent quarterly revenue

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Alfa presents quarterly revenue data in a clear, descending-order table. In contrast, ChatGPT provides a general list of companies with descriptions but lacks numerical data to substantiate its output.

Look at SPY, score each stock based on their past 3 month price momentum. Output this list ranked from highest momentum to lowest momentum. For the top 5 momentum and bottom 5 momentum names, read news and SEC filings including 8-k filings, briefly summarize major events that impacted the company over the past 3 months.

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Alfa accurately identifies the top and bottom 5 performers based on price momentum data and delivers a more detailed analysis of major events affecting these companies using more datasets and sources than ChatGPT.