In today's ever-evolving world, the potency of Artificial Intelligence (AI), especially Large Language Models (LLMs) like GPT, can't be understated. From language translation to summarization and beyond, the versatility of LLMs is remarkable. Yet, a crucial shortcoming exists: understanding a dynamic world in real-time.

The Challenge with LLMs

Despite their prowess, LLMs aren't inherently equipped to decipher the torrents of content gushing daily from multilingual news channels, myriad social platforms, the intricate labyrinths of the deep and dark web, and other dynamic text-based feeds. They have an incomplete picture in both their training data and the data they can access.

This limitation is starkly evident in time-sensitive domains like fraud, geopolitics, security, supply chain and market intelligence.

The static nature of LLMs means they're a snapshot of the past, often tied to a specific training period. For instance, ask about the hypothetical "SVB collapse," and GPT-4 might return:

"As of my last update in September 2021, there hasn't been any event or news related to a collapse of SVB (Silicon Valley Bank)."

Furthermore, without inherent mapping or timeline functionalities, LLMs can struggle to interconnect events, trends, entities and locations.

Methods like retrieval augmented generation (RAGs) help use real-time information but for only the pool. GPT’s Bing integration, Google’s Bard and X’s Grok can each access different sources but these are limited. The challenge is pulling the right data together to answer questions or to provide relevant insights in real-time, proactively.

Overwatch Data: Revitalizing Real-time Information

However, technological roadblocks are merely invitations for innovation.

At Overwatch Data, we've pioneered a system that marries the ingenuity of chat experiences with live data processing. Imagine wanting real-time alerts on cybercriminal activities or asking a platform for “companies that unveiled new energy strategies last week”. With our platform, such granular, dynamic queries are no longer aspirational but achievable.

Our process:

1. Bringing together a common operating picture of data across platforms and sources to leverage both the emerging social narratives, dark web sources and authoritative publications
2. Light-weight models sift through the data deluge, narrowing down to the most pertinent content to what matters to your interests, across languages
3. Intricate LLMs refine this subset with greater precision
4. Event clustering & entity extraction: every piece of information gets categorized into events, like "discussions about Prigozhin’s death". Simultaneously, we identify key entities—be it people, organizations, or places—to derive context. For instance, understanding how a political event in Niger might sway global uranium trade dynamics.
5. Focus on context and actionability: is there additional information that would make our response more actionable to you based on what you’re interested in e.g. this new fraud technique specifically impacts your onboarding process at point X - you should consider the following remediations

The culmination? Our platform can answer vital questions about live or recent events and narratives without the need for elaborate prompt engineering. This includes its origins, key players, locales, and historical context, similar to how a human analyst would present.

Moreover, our API integration offers vast automation opportunities. For businesses wanting real-time updates on companies embroiled in financial controversies, our platform can distill the information, letting organizations run checks against their clientele.

Explainable AI

As a decision maker you own the outcome, regardless of the tools you use. Black box answers are hard to verify and trust for decision assistance. For leaders whose decisions need to be grounded in evidence, answers that are confidently wrong some of the time and can't be double checked are hard to use. This is why we’re committed to transparent systems that show the underlying data sources.

Visualizing & Contextualizing Data

The true magic emerges when this data undergoes visualization. An incident in a city isn't just a standalone event. Our platform layers contextual datasets, offering insights about the city's demographics, local businesses, logistics, and relevant risk indicators.

Overwatch Data simplifies this journey for the decision maker. With our user-friendly, zero-code platform, staying abreast of the world's pulse—its risks and opportunities—becomes intuitive and efficient.