Legacy architecture and an overwhelming amount of unstructured data make it difficult for finance professionals to perform forecasting, increase returns, and manage risk. When sound investment decisions rely on machine learning models with human-level precision and recall, Primer Engines instantly deliver performant, fast, and scalable AI. Engines are trained and tuned to work on domain-specific data for finance. They empower financial service companies to quickly extract, surface and connect the hard-to-find, but crucial information needed to advance their business.
A fintech company tested multiple leading NLP solutions — Primer outscored them all across all key performance metrics. Read the blog post
Rapidly uncover trading opportunities hidden in 10-Ks, analyst notes, publicly available research, and news sources
Traders pore through massive amounts of industry and historical data every day to identify trading opportunities and get that extra edge that will maximize their returns. With Primer Engines, traders can connect engines together to build custom data processing pipelines and find hidden connections across proprietary and public resources. Here are a few sample Engine pipelines:
Automate the generation and maintenance of entity profiles
Each day, analysts spend hours looking for new information about people, places, and organizations to uncover previously unknown information and connections. For example, each September, thousands of diplomats converge in New York City for the United Nations General Assembly. Analysts can construct their own pipeline of Primer Engines to help them better understand diplomatic activities:
Named Entity Recognition (NER): Use publicly available information to generate a comprehensive list of the thousands of foreign diplomats visiting New York for the UN General Assembly.
Relation Extraction: Automatically generate a list of events, locations, and key meetings being attended by foreign diplomats.
Topic Modeling: Automatically process all of the textual content relevant to the General Assembly to identify emerging issues or previously unknown areas of focus.
Quote Attribution: Process millions of pieces of content each day to understand what each diplomat is saying.
Claims Detection & Dispute Resolution: Extract the specific claims being made by diplomats, cluster similar claims, and automatically determine Side A and Side B of disputes.
Event Detection: Detect and geolocate key events, and generate lists of attendees, associated organizations, and more.
Summarization: Summarize in paragraphs or bullet points what happened during key diplomatic functions.
Rapidly reveal unknown patterns and connections
Over the past years, strategic competitors of the U.S. have accelerated overseas investments to extend their global influence. Because of the unprecedented scale of this activity — captured across media reports, financial reporting, and social media — intelligence analysts need the ability to automatically generate structured datasets and integrate them into their knowledge base. With Primer Engines, analysts now have the building blocks to create their own data processing pipeline:
Named Entity Recognition (NER): Identify state-sponsored companies, their subsidiaries, and associated companies across several years of English, Russian, and Chinese-language news data.
Relation Extraction: Identify and geolocate locations where these organizations were mentioned, as well as their corporate officers, key products, corporate initiatives, and more.
Event Detection and Event Linking: Detect and cluster documents describing events relevant to organizations of interest.
Event Classification: Classify events relevant to these organizations to identify mergers and acquisitions or key investments
Summarization: Automatically generate human-quality reports on events related to state-sponsored companies.
Accelerate detection and monitoring of influence campaigns
Analysts and operators have the near impossible task of detecting information and influence operations across billions of social media posts, and establishing the origin and intent quickly enough to take action. With Primer Engines, they can leverage a pipeline of Engines that are specifically trained and tuned to rapidly detect indicators that foreign adversaries are pushing a malign narrative:
Claims Detection & Dispute Resolution: Identify disputed information across billions of pieces of content, and surface who is involved in disagreements over key facts.
Synthetic Text Detection: Detect content that is being automatically generated by machines and not written by human actors.
Bot Detection: Detect content that has been algorithmically amplified.
Topic Modeling: Characterize thousands of conversations to identify emerging narratives.
Event Classification: Classify indicators and warnings of emerging events of interest, such as narratives related to the U.S. and the South China Sea.