The New York-based startup Cognaize has secured $18 million in funding to develop its platform for processing unstructured data in financial artificial intelligence (AI) applications. The approach involves deep learning technology trained on financial models, augmented with human input to enhance the final product. With the additional funds, Cognaize intends to expand its workforce, conduct new research and development initiatives, and introduce new products. Argonautic Ventures led the investment round, with participation from Metaplanet and other supporters.
While AI has made significant impacts in the banking sector, most efforts have concentrated on structured data. Cognaize’s platform aims to harness the vast potential of unstructured data for gaining valuable insights. The company believes that despite the abundance of data available to the financial sector, only a fraction of it (the structured part) is utilized to enhance services, understand market conditions, and discern customer preferences. Cognaize employs deep learning trained on financial models and a vast collection of documents to address this issue.
Cognaize’s infrastructure is built on deep learning tools exclusively trained on financial models. The platform accesses 1.3 million documents, potentially containing numerous crucial pieces of information that require expert interpretation. Examples of these documents include loan applications, SEC filings, environmental, social, and governance (ESG) documents, presentations, and trustee reports.
The company has designed a platform that leverages deep learning trained on financial models and a diverse array of documents, totaling over 1.3 million, that may contain important information necessitating skilled interpretation. These documents cover a range of materials such as SEC filings, ESG documents, presentations, trustee reports, and loan applications.
Cognaize acknowledges that while AI has the potential to evolve in unprecedented ways, it can never fully replace humans. Hence, the platform incorporates “humans in the loop” to refine the work. Financial analysts and other human personnel use the platform to correct readings and make decisions based on the results.
Vahe Andonians is the founder, CTO, and Chief Product Officer of Cognaize. He previously founded a fintech company focused on analytics and risk management for credit investments, which was acquired by Moody’s. Andonians envisions that AI can complement human abilities by performing tasks beyond human capabilities.
Cognaize’s client base includes two of the three largest credit rating agencies, major insurance providers, and banks. These entities leverage the platform to process a large volume of unstructured financial data, leading to enhanced decision-making, risk assessment, and the unveiling of patterns and trends previously obscured by complexity and human error.
The success of AI-focused startups like Cognaize reflects a prominent trend in the industry. There is a notable surge in specialist entities focusing on specific fields and use cases, despite the proliferation of companies building general knowledge graphs in AI and creating massive language models. This trend suggests a shift towards prioritizing quality over breadth.
Investors are likely drawn to these specialists because they are expected to maintain more personalized communication with their customers and offer tailored approaches that yield superior results. Additionally, their models may be more cost-effective to operate due to their reduced parameters, requiring less processing power.
Viken Douzdjian, Managing Partner at Argonautic Ventures, expressed excitement about partnering with Cognaize, recognizing the transformative potential of AI and large language models in finance. The investors have unwavering confidence in Cognaize’s team to shape the future application of AI in the financial sector.
Cognaize is an intriguing startup that has demonstrated consistent, quantifiable benefits from artificial intelligence in the banking sector. It stands out for its ability to extract insights from unstructured data, making it a company to closely monitor as it continues to develop its technology and expand its offerings in the financial sector.
Frequently Asked Questions
Q. What is Cognaize, and what is its recent funding announcement about?
A. Cognaize is a New York-based startup focused on developing an unstructured data processing platform for financial artificial intelligence (AI) applications. The company recently raised $18 million in funding to further develop its platform, which combines deep learning technology with human input to extract useful insights from the vast amounts of unstructured data in the financial sector.
Q. What sets Cognaize’s platform apart from other AI efforts in the banking industry?
A. Unlike many AI initiatives that primarily focus on structured data, Cognaize’s platform is designed to leverage the enormous potential of unstructured data in the financial sector. It operates under the belief that only a small fraction of available data is currently used to improve services, market understanding, and customer preferences.
Q. How does Cognaize’s platform process unstructured financial data?
A. Cognaize’s platform is built on deep learning tools trained on financial models. It analyzes over 1.3 million documents that may contain valuable information, such as loan applications, SEC filings, ESG documents, presentations, and trustee reports. These “cells” of information require a trained eye to interpret accurately.
Q. How does Cognaize incorporate human input into its platform?
A. Recognizing that AI cannot entirely replace humans, Cognaize includes a “humans in the loop” approach. Financial analysts and other human workers utilize the platform to fine-tune the readings, draw conclusions, and make decisions based on the results.
Q. Who is Vahe Andonians, and what is his vision for AI in finance?
A. Vahe Andonians is the founder, CTO, and Chief Product Officer of Cognaize. He believes that AI can complement human capabilities by performing tasks beyond human abilities. His prior fintech venture, which focused on analytics and risk management for credit investments, was acquired by Moody’s.
Q. Which industries and companies are utilizing Cognaize’s platform?
A. Cognaize’s clients include two of the three largest credit rating agencies, major insurance providers, and banks. These companies use the platform to process vast amounts of unstructured financial data, leading to better decision-making, risk assessment, and discovery of hidden patterns and trends.
Q. Why are investors interested in AI-focused startups like Cognaize?
A. Investors recognize the potential of specialists like Cognaize, who focus on specific fields and use cases in AI. Tailored approaches offer better results and training for a company’s unique needs and may be less expensive to run with fewer parameters in their large language models.
Q. What do the lead investors, Argonautic Ventures and Metaplanet, have to say about Cognaize?
A. Argonautic Ventures believes in the transformative power of AI and large language models (LLMs) in finance and has faith in Cognaize’s team to shape AI’s future in the financial sector. Metaplanet, another investor, praises Cognaize for harnessing the power of AI and its unmatched technology roadmap, leading to significant cost reductions and a competitive edge in the financial industry.
Q. Why is Cognaize considered an exciting startup in the banking sector?
A. Cognaize stands out for providing consistent, quantifiable benefits from artificial intelligence in the banking sector. Its platform’s ability to unlock insights from unstructured data sets it apart in the industry, making it an innovative company to watch closely.
Q. What does the future hold for Cognaize and its platform?
A. Cognaize’s future roadmap involves further development and expansion of its technology, enabling even more applications and benefits for the financial sector. The company’s AI-driven approach is poised to reshape how data is utilized in finance and bring valuable insights to businesses and decision-makers in the industry.
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