Buy-side professionals are inundated with data, but they need real-time, trusted financial information and, critically, a way to make sense of it quickly, according to Armando Gonzalez, CEO of RavenPack.
“The problem is that this data is often scattered across public sources, locked behind paywalls, or siloed within organizations,” he told Traders Magazine.
To address this issue, RavenPack has launched Bigdata.com, an advanced AI platform set to transform financial research and decision making.
“With Bigdata.com you can access it and “chat” with all of it,” Gonzalez said.
Bigdata.com’s powerful API and real-time research assistant let users converse directly with billions of financial documents, create custom research tools, automate tasks, and access real-time data.
“AI tools promised a revolution in finance but often fell short. Financial professionals cannot work with generic, outdated, or inaccurate information,” Gonzalez said.
He added that Bigdata.com changes this by offering reliable, transparent AI-driven research that’s “actually useful”.
“Our platform doesn’t just provide information; it automates and accelerates the research process,” he stressed.
What once took days or weeks can now be done in hours, because teams can now interact directly with a universe of curated financial data in real time, Gonzalez explained.
For example, teams combing through earnings reports can now instantly analyze and summarize key metrics, like revenue or EPS, and spot any deviations from expectations, which helps to quickly reassess risk exposure or rebalance portfolios to mitigate risk, he said.
The development of Bigdata.com is backed by a $20 million investment led by GP Bullhound and spearheaded by a team of former quantitative analysts and data scientists from leading financial institutions.
Since launching in Beta in July 2024, over 40 leading financial institutions have been deploying Bigdata.com.
This includes four major global investment banks, a top five credit-focused hedge fund, and 10 of the largest asset management firms worldwide.
“Our +20-year track record speaks for itself, with clients like JPMorgan Chase, UBS, and the US Federal Reserve. Now, we’re making this high-quality data available to everyone through a real-time research platform,” Gonzalez said.
“Our “data-first” approach integrates over two decades of expertise with real-time, curated insights, ensuring accuracy and traceability for every piece of information,” he added.
Gonzalez added that they also built a finance-specific taxonomy from scratch, ensuring that the insights are relevant and use precise financial terminology.
He said that their Financial Knowledge Graph, with 12M+ entities, helps users filter and discover critical information, and our domain-specific embeddings capture the nuances of financial language.
Additionally, users can create custom watchlists with specific portfolios or themes or “chat” with specific datasets, he added.
“This level of personalization, transparency, and reliability is something you won’t find in other AI platforms,” Gonzalez argued.
According to Gonzalez, the AI platform boosts financial research efficiency tenfold: “Our claim of a 10x efficiency boost is grounded in real results from our beta users. Financial firms are slashing the time it takes to go from research to action.”
He further said that tasks that once took days or weeks – like analyzing earnings, monitoring portfolios or building investment theses – can now be completed in hours.
For example, he said, clients use our system to analyze which companies may do better under a Trump presidency versus a Harris victory in just a few hours, a task that would have taken a team at least one week.
“This kind of speed enables buy-side firms to reposition portfolios or make allocation decisions in real time, capturing opportunities before anyone else. The goal isn’t to cut costs or replace people, but to help them achieve much more with the same resources,” he commented.
Bigdata.com offers a vast range of financial data, including web content, premium news, earnings reports, regulatory filings, pricing data, estimates, and sentiment scores.
Users can also upload and extract insights from their own files or customize their research by “chatting” with specific datasets for tailored insights, and we’re constantly expanding this universe.
Gonzalez said that they’ ’re focused on enhancing AI’s practical utility in finance.
“Soon, we’ll add alternative data sources like social media trends, satellite imagery, and geolocation insights,” he said.
“We’re also developing more specialized AI agents to handle financial tasks with unprecedented precision,” he concluded.
