Raj Neervannan is the CTO and co-founder of AlphaSense, a ground-breaking AI-based market intelligence search engine used by over 2,000 investment firms and corporations globally. A visionary technologist and entrepreneur of multiple venture-backed firms, Raj has previously led the development of financial software products used across numerous Fortune 500 companies. Mr. Neervannan splits his time between offices in the U.S., India, and Finland.
Finding the right information to make critical business decisions is difficult. It requires understanding your own business, your competitors, and the market you both operate in—then synthesizing and making sense of it all to make a well-informed decision. This requires time and keen analytical skills, with each decision building on the quality of the prior one. Technology is supposed to help, but doesn’t always do the trick.
It’s no wonder this is the case. Most of the information on the internet takes the form of unstructured information—everything from transcripts to exclusive content to gated reports. This content is hard to search through with conventional web search engines, which were primarily designed for traditional web content and to capture advertising dollars rather than relevant business information. Similarly, other traditional enterprise search solutions don’t quite work either—they have a hard time filtering the signal from the noise and often fail to expand on the intent, as they lack the contextual and semantic understanding to do so. Analysts, strategists, and other decision-makers using conventional search and these other products end up wasting time, thus missing out on mission-critical information found elsewhere.
Moreover, in our post-print world, many kinds of useful digital content show up in disparate, even surprising places, such as trade journals, press releases, event transcripts, expert call transcripts, company presentations, and analyst reports. The breadth of these sources can be daunting to any knowledge professional.
Between these two major pitfalls of information in the digital age—lack of structure, and overwhelming breadth of sources—knowledge professionals are bound to miss vital information critical to their decision. And the compounded effect of analyst after analyst missing critical insights and committing poor or delayed decisions is extremely detrimental to a company’s bottom line.
This is why contextual, competitive intelligence tools are so important. They allow users to wade through waves of information for smarter, faster, and more confident decision-making. This gives companies an advantage against competitors by preventing costly mistakes, ensuring better outcomes, and enabling more accurate future planning.
Sophisticated augmented intelligence platforms, driven by AI and expert insights, empower businesses to create order from chaos, making sense of complicated, unstructured information. For instance, unlike traditional search engines that point readers to entire pages, advanced tools like AlphaSense extracts relevant snippets, giving readers more context without the need to scan the entire document. This way, users glean the right information more efficiently than they would with conventional web search or with business intelligence tools with less-developed tech and design. What makes it special is the platform understands user query intent and guides users to the right answers, extracting insights that allow them to make smarter decisions with confidence and speed.
Business users often have a nuanced understanding of a topic that traditional search engines may not be able to capture. For example, let’s say that you wanted to learn more about driverless cars. When searching the phrase “autonomous vehicles”, traditional search engines may only surface articles that use the exact literal keyword. Often, searches have different synonyms, like “self-driving” or “driverless” or “cars” or “trucks.” Search engines that don’t focus on the human semantics of the search miss out on crucial data.
Hence, it is critical for search query to surface results that include that specific term, as well as all the synonyms and other real-world examples that people associate it with. Novel AI-based search technology applies natural language processing, search proximity, company tagging, sentiment analysis, topic modeling, and knowledge extraction, and its understanding of the nature of documents to optimize research for professional users. The research process, as it is generally conducted now with traditional search engines, can block your ability to swiftly analyze a topic, market, company, or theme.
Certainly, getting the right information can be like finding a needle in a haystack. And at the end of the day, information is just a means to an end—to enable people and businesses to succeed. To thrive in today’s information vortex businesses must embrace the next generation of intelligence platforms for all their relevant information needs.