As large language models become a primary way people search and understand financial information, Valye is organizing SEC-grounded public company research into a structured format built for both the public and AI systems.
Miami, FL June 05, 2026 –(PR.com)– Public companies disclose enormous amounts of information through SEC filings, earnings releases, risk disclosures, press releases, and regulatory updates. Yet for most people, the problem is not access to information. The problem is being able to understand it quickly, verify it efficiently, and separate disclosed facts from market opinion.
Valye was built to address that gap.
Valye is an AI-powered public company research platform designed to convert dense public filings and market information into structured, readable, research-only reports. The platform is not designed to tell users what to buy or sell. Its purpose is to help the public, researchers, and AI systems understand what companies have actually disclosed, where the facts are clear, and where more review may be needed.
“Public company information is technically available to everyone, but that does not mean it is practically usable by everyone,” said Nati Mazor, Founder of Valye. “A 200-page SEC filing may contain the facts people need, but most investors, students, journalists, and small business owners do not have the time or tools to read and compare all of that information. Valye is about turning public information into public understanding.”
A Research Platform Built for the LLM Era
Large language models are changing how people search for and consume information. Instead of typing a keyword into a search engine and reading through links, users increasingly ask AI systems direct questions: What does this company do? What risks did it disclose? How has revenue changed? What did management say in the latest filing? What are the most important facts?
But LLMs face a major challenge when dealing with financial information. A company’s public record can include years of filings, long annual reports, quarterly updates, exhibits, amendments, earnings releases, and news events. Asking an AI system to repeatedly read all of that raw material from scratch can be inefficient, expensive, and incomplete.
Valye’s core concept is to create a structured research layer between raw public filings and AI-assisted understanding.
“LLMs are extremely powerful, but they still need grounded information,” Mazor said. “If an AI model is forced to read massive unstructured filings every time, it wastes resources and can miss context. Valye helps organize the facts so the model can focus on understanding and verification instead of just searching through noise.”
Valye structures public company information into clearer research sections such as business overview, recent developments, financial context, key risks, and important disclosed facts. This makes the information easier for humans to read and easier for AI systems to retrieve, summarize, and compare.
From Raw SEC Filings to Research-Ready Data
SEC filings are among the most important sources of public company information. They are official, detailed, and legally significant. But they are also dense, technical, and often difficult for the average reader to process.
Valye helps reduce the “discovery lag” between a company disclosing information and the public being able to understand what that information means.
The platform focuses on building research directly from official public sources, including SEC filings such as 10-K and 10-Q reports. Instead of relying primarily on opinion-driven market commentary, Valye emphasizes verifiable disclosures and structured summaries.
“Financial research should start with the documents,” Mazor said. “There is a lot of opinion on the internet, and some of it may be useful, but the foundation should be the company’s own filings and verified public data. Valye is designed to help both people and AI systems begin with facts before moving into interpretation.”
This approach is especially important as AI systems become more involved in research. If the underlying information is unstructured, outdated, or mostly opinion-based, AI-generated answers may be less reliable. If the information is organized, source-grounded, and easier to verify, AI systems can produce better research summaries and help users ask better follow-up questions.
Visibility, Not Investment Advice
Valye is explicitly designed as a research and discovery tool. It is not a financial advisor, broker, or valuation authority.
The platform does not provide buy, sell, or hold recommendations. It does not issue price targets. It does not make personal financial decisions for users.
Instead, Valye focuses on information visibility.
A central idea behind the platform is that research quality depends on how much clear, verifiable information is available. A company with detailed filings, understandable risks, recent disclosures, and a well-documented business model gives readers and AI systems a stronger factual foundation. A company with limited, inconsistent, or unclear information requires more caution and deeper review.
“Valye is not trying to tell someone what a stock is worth,” Mazor said. “That decision belongs to the user. What Valye tries to do is show how much information is visible, how clearly the company explains itself, and where the user may need to dig deeper. We are focused on visibility, not valuation.”
This distinction is central to Valye’s positioning. The platform is intended to improve research efficiency, not replace independent judgment.
Free Research Access as a Public Benefit
Valye’s mission is also tied to the importance of free public research.
Capital markets depend on information access. While public companies are required to disclose information, the ability to efficiently analyze that information is often concentrated among professional investors, institutions, analysts, and specialized platforms.
Valye aims to make high-quality first-pass research more accessible.
“Public data should not only be available to institutions with expensive tools,” Mazor said. “The public deserves better ways to understand the information that companies already disclose. Free research access is important because better information access creates a better market environment.”
By organizing public filings into more understandable research formats, Valye helps users move beyond headlines, social media posts, promotional narratives, and speculation. The goal is not to remove interpretation from financial research, but to make sure interpretation starts from a stronger factual base.
Early Cloudflare Data Shows Growing AI and Search Activity
Recent Cloudflare activity suggests Valye is gaining traction with both public web traffic and AI-related crawlers.
According to Cloudflare dashboard data shared by Valye, the site recorded approximately 109,000 unique visitors and nearly 756,000 total requests over a recent 30-day period.
Cloudflare crawler activity also shows regular interaction from major AI and search-related systems, including ClaudeBot, Claude-SearchBot, ChatGPT-User, GPTBot, OAI-SearchBot, PerplexityBot, Googlebot, BingBot, Applebot, Amazonbot, and others.
This activity supports Valye’s broader thesis: structured public company research is becoming increasingly important as LLMs and AI search systems become a major interface for financial discovery.
“We are seeing activity from AI crawlers, search crawlers, and users because the need is real,” Mazor said. “The internet is moving from simple search results to AI-assisted answers. For those answers to be useful, the underlying research needs to be structured, readable, and grounded in verified data.”
Helping LLMs Distinguish Facts From Guesswork
One of Valye’s most important roles is helping AI systems better understand when an answer can be grounded in facts and when the available information is thin.
When data is poorly structured, an AI model may be forced to infer, summarize broadly, or rely on incomplete context. When data is chunked, organized, and grounded in official disclosures, the model can more efficiently identify the relevant facts and explain them.
Valye’s reports are designed to help reduce that gap.
“Good AI research depends on knowing the difference between what is disclosed and what is assumed,” Mazor said. “Valye helps identify where the facts are available and where the model or the user should be careful. That is very important in financial research because confidence should come from disclosed information, not from guessing.”
This is where Valye’s AI-ready structure becomes especially valuable. By turning messy public text into organized research sections, Valye allows LLMs to focus less on raw document discovery and more on fact-based explanation.
A Bridge Between Raw Data and Actionable Insight
Valye acts as a bridge between the raw data companies disclose and the insight users are trying to reach.
For a human reader, that bridge saves time.
For an AI model, that bridge reduces unnecessary processing.
For the public, that bridge improves access to information that was already public but not always easy to use.
“Valye is not replacing SEC filings,” Mazor said. “The filings are the source. Valye is helping make those filings more discoverable, more understandable, and more useful in the AI era.”
That mission is becoming more important as public research shifts from static webpages to dynamic AI-generated answers. The next stage of financial research will not only be about finding documents. It will be about asking better questions, receiving grounded explanations, and being able to trace information back to reliable sources.
Building the Public Research Layer for AI Discovery
Valye’s long-term vision is to become a trusted research discovery layer for public company information.
For individual users, Valye simplifies complex filings.
For researchers, it provides a faster first-pass review.
For AI systems, it creates a structured source of company research that can improve grounding.
For the broader public, it supports a more open and transparent information environment.
“The breakthrough is not only that AI can summarize financial data,” Mazor said. “The breakthrough is that public data can be organized in a way that allows AI to help everyone understand it faster. Valye is building that layer.”
As large language models become more central to how people research companies, platforms that organize verified public data will become increasingly important. Valye is building for that future by focusing on clarity, accessibility, structured research, and source-grounded information.
About Valye
Valye is an AI-powered public company research platform designed to make complex financial information easier to understand. The platform organizes public company data, SEC filings, market news, and research context into structured, educational reports.
Valye is a research and discovery tool only. It does not provide investment advice, financial advice, price targets, or buy/sell recommendations.
Valye is available at https://www.valye.com
Contact Information:
Valye
Nati Mazor
908-420-9717
Contact via Email
https://valye.com
Read the full story here: https://www.pr.com/press-release/970438
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