Reco-NLQ (Cutting edge natural language querying platform)

Home Reco-NLQ (Cutting edge natural language querying platform)


Explore and have a deeper understanding of data without the hassle of using complex query knowledge. Our Natural Language Querying (NLQ) enables users to perform deeper analytics of data by simply asking queries in chat or voice in a natural conversation manner. The NLP engine breaks down the user’s query and extracts the meaning of the query; based on that the NLQ system uses machine learning algorithms to generate a response based on the available data.
Our powerful NLQ system helps businesses in faster decision-making, improves data quality helps in better team collaboration, and saves cost.

Latest Posts

How to Spot Fake Bank Statements

With evolving digital transactions and sophisticated fraud techniques, the need for robust fraud detection mechanisms is equally increasing. One area where this is particularly pertinent is in identifying fake bank statements, a common tool fraudsters use to manipulate financial information.    Imagine a slow and error-prone verification process trying to interpret the increasingly sophisticated tactics […]

Top Trends in Investment Banking

The investment banking sector is currently grappling with several challenges. These include dealing with capital charges, digital adoption, rigid cost structure, intricate and layered technological stacks, and increased regulatory demands. As a result, various investment banks shifted their emphasis from conventional underwriting services to concentrate more on alternatives such as mergers and acquisitions and fundraising […]

Leveraging AI for Advanced Lending Fraud Detection

Fraud has plagued the lending industry for many years. Fraudulent behavior in lending can take many forms, including identity theft, loan stacking, and money laundering. To combat these issues, lenders increasingly turn to artificial intelligence (AI) for fraud detection. AI has the potential to transform fraud detection in lending by enabling lenders to analyze vast […]