NewsCatcher: Structuring Real-World Web Data
In a world where information is abundant but fragmented, NewsCatcher positions itself as a bridge between raw web content and structured, actionable intelligence. Founded in 2021 and headquartered in Kyiv, the company has set out to solve a problem that has long been overlooked: how to transform the vast, unstructured web into a usable database of real-world events.
With a team of 22 and roots in deep data engineering expertise, NewsCatcher is not merely another search provider. Instead, it operates at the intersection of data infrastructure, artificial intelligence, and real-time analytics. Its mission is ambitious yet precise—to make the web queryable not just for humans, but for machines, systems, and decision-makers who rely on complete and accurate datasets.
At the heart of this mission lies its flagship product, CatchAll—a recall-first web search API designed to fundamentally rethink how information is retrieved and used.
Why Do Traditional Search Engines Fall Short?
Most traditional search engines, including widely used platforms like Google, are optimized for human consumption. They prioritize speed, ranking, and relevance based on popularity or authority. This works well for simple, fact-based queries such as identifying a CEO or finding a single news article.
However, the limitations become apparent when dealing with complex, multi-source questions. Consider queries like:
- All regulatory actions affecting a specific industry
- Every cybersecurity incident reported within a timeframe
- All funding rounds in a niche market
These are not “single-answer” questions. Instead, they require aggregating dozens, hundreds, or even thousands of data points scattered across the web.
Traditional systems fail here because they optimize for ranking rather than completeness. If 200 relevant events exist but only 5 are surfaced, the system achieves a recall rate of just 2.5%. For industries like finance, risk analysis, or cybersecurity, such gaps are not just inconvenient—they are dangerous.
What Makes CatchAll a Recall-First Search API?
CatchAll introduces a fundamentally different paradigm: recall-first search. Instead of asking, “What are the best results?” it asks, “What are all the relevant results?”
This shift changes everything.
The system begins by pulling a massive candidate set—often tens of thousands of web pages—from NewsCatcher’s proprietary index. This index continuously scans millions of articles and public sources across the globe, ensuring that no relevant signal is missed.
Once the data is collected, CatchAll performs several critical steps:
- Validating which pages truly match the query criteria
- Extracting structured fields such as companies, dates, locations, and actions
- Normalizing inconsistent data formats
- Deduplicating overlapping information
The result is not a list of links. Instead, it is a clean, structured dataset—something that did not previously exist in a usable form.
How Does CatchAll Turn Data into Structured Intelligence?
The true innovation of CatchAll lies in its ability to convert messy, unstructured content into structured intelligence. This transformation is what enables entirely new use cases.
Rather than forcing analysts to manually sift through articles, the system outputs ready-to-use records. Each record can include:
- Entities (companies, organizations, individuals)
- Event types (funding, regulation, expansion, incidents)
- Dates and timelines
- Geographic locations
- Quantitative data (amounts, metrics, values)
This structured output can be directly integrated into:
- AI agents
- Monitoring systems
- Analytics dashboards
- Market intelligence platforms
In essence, CatchAll turns the web into a continuously updating database of real-world events—one that can be queried, filtered, and analyzed programmatically.
Who Benefits Most from This Technology?
CatchAll is not built for casual browsing. Its primary users are developers, data teams, and organizations that require comprehensive and reliable datasets.
Typical use cases include:
- Financial analysis: Tracking funding rounds, mergers, and acquisitions
- Regulatory monitoring: Identifying policy changes across jurisdictions
- Cybersecurity intelligence: Aggregating incident reports in real time
- Market research: Mapping competitor activity and expansion strategies
For these users, the difference between partial and complete data is critical. A missed signal could mean a missed opportunity—or an unanticipated risk.
By prioritizing recall, CatchAll ensures that users are not just informed, but fully informed.
Why Haven’t AI Models Solved This Problem Yet?
Despite the rise of advanced AI systems, including large language models like ChatGPT, the challenge of comprehensive data retrieval remains unsolved.
These models typically operate by sampling information. They retrieve a limited number of documents, process them within context constraints, and generate responses based on partial data. While this approach works for summarization or general knowledge tasks, it struggles with exhaustive queries.
Key limitations include:
- Context window constraints
- Sequential document processing
- Inability to guarantee completeness
As a result, even the most advanced AI systems cannot reliably answer “long-list” questions where completeness is essential.
CatchAll addresses this gap by focusing not on generation, but on retrieval and structuring—providing the raw material that AI systems need to function effectively.
What Is the Story Behind NewsCatcher’s Founders?
The foundation of NewsCatcher is rooted in a long-standing partnership between its co-founders, Artem Bugara and Maksym Sugonyaka.
Having known each other for nearly two decades, the duo combines complementary expertise in data engineering, finance, and large-scale systems. Artem, who serves as CEO, brings experience from leading data engineering teams in high-stakes industries such as aviation and energy insurance. His background in econometrics provides a strong analytical foundation for understanding risk and data-driven decision-making.
Maksym, the CTO, took a less conventional path. After leaving a stable job early in his career, he pursued entrepreneurship and became a self-taught data engineer. His technical leadership has been instrumental in building the infrastructure that powers NewsCatcher’s products.
Together, they have created a company that reflects both strategic vision and technical depth.
How Did NewsCatcher Evolve Into What It Is Today?
NewsCatcher did not begin with CatchAll. The company’s journey started in 2020 as a bootstrapped news API designed for startups. This initial product focused on providing accessible, self-serve access to news data.
Over time, the company expanded into enterprise solutions, serving high-profile clients such as:
- The U.S. Department of State
- Transparency International
- Samsung
These engagements helped refine the company’s infrastructure, enabling it to handle large-scale, mission-critical data workflows.
CatchAll represents a return to the company’s self-serve roots—but with significantly more advanced capabilities. It leverages the same robust infrastructure, now optimized for the emerging ecosystem of AI agents and automated systems.
What Does the Future Hold for Structured Web Data?
The rise of AI agents, automation, and real-time analytics is reshaping how organizations interact with information. In this context, structured data is becoming more valuable than ever.
NewsCatcher’s vision aligns closely with this trend. By transforming the web into a structured database of events, the company is enabling:
- Continuous monitoring instead of one-time searches
- Automated workflows driven by real-time data
- More accurate and comprehensive decision-making
As industries increasingly rely on data-driven insights, the demand for high-recall, structured information systems is likely to grow.
CatchAll positions NewsCatcher at the forefront of this shift—not as a competitor to traditional search engines, but as a complementary layer designed for a new generation of use cases.
Can the Web Truly Become a Structured Database?
The idea of turning the web into a structured database may sound ambitious, but NewsCatcher is already demonstrating its feasibility.
By combining large-scale indexing, validation, and data extraction, the company is redefining what search can achieve. Instead of navigating through pages of links, users can directly access the information they need in a structured, actionable format.
This approach does not just improve efficiency—it changes the nature of information access itself.
In a world where data is both abundant and overwhelming, NewsCatcher offers a compelling vision: one where every relevant signal is captured, organized, and made instantly usable.
And in that vision, the web is no longer just a collection of pages—it becomes a living, queryable database of everything happening in the real world.