An Inside View of Coginov’s AI Lab
An Inside View of Coginov’s AI Lab
Our team is made up of artificial intelligence (AI) scientists, AI engineers, linguists, and knowledgeable customer-care and sales professionals. We possess a wide knowledge and experience in natural language processing (NLP), computational linguistics, and semantic technologies.
With such a deep bench of experts, it was natural to combine machine learning (ML) and NLP approaches in developing a platform that offers contextual search of enterprise repositories and enhanced analytics, all to enable sharper insights and enhanced enterprise strategy.
Contrary to the bulk of vendors in the text-based data analysis market, we have dual areas of expertise – NLP and ML – and our technology is defined by applying the combination of these powerful approaches for optimal content analysis. Our semantic analysis, based on industry specific dictionaries, combines with robust machine learning algorithms that work to identify meaning and present results in context.
We apply machine learning in each step of the processing of unstructured data. This ML-based approach helps to greatly widen the funnel of usable material. Specifically, our ML-first approach renders unstructured data from content repositories into human and machine-readable semantic assets.
We can then build analytics and language modeling from those semantic assets, which is subsequently applied to perform pattern extraction and analysis of named entities, key concepts, and singular alphanumerical patterns. These semantic knowledge representation structures, generated by ML, comply with state-of-the-art ontological standards that make use of innovative language models.
Coginov’s AI framework leverages a stacked model methodology that combines an associative memory model with three ML approaches, one of which is based on a powerful, deep-learning neural network. Our ML framework generates meaningful context by combining best practices in language models and topological data extraction methods to identify the semiotic value in unstructured data repositories.
Nearly 80% of enterprise data is unstructured — from emails and word processing documents to multimedia, PDF files, spreadsheets, messaging content, graphics, social media posts, and more – meaning that it’s very challenging to mine it for useful insights.
For a long time, businesses relied on limited, structured data from spreadsheets and tables to drive business decisions. Capabilities have gradually increased, so that now there are many data mining and electronic document and records management (EDRM) solutions that do a good job of collecting data and monitoring for occurrences of keywords (brand names, product names, etc.).
But most of these solutions leave the end-user with the task of manually figuring out how to proceed with analysis, and, from this flood of data, attempt to understand what the appropriate calls to action are within their organization.
At Coginov, we understand the true value of unstructured data and the need to not only capture it but contextualize it. Our technology goes much farther than issuing reports on semantic concepts, entities occurrences, and weighting – it delivers accurate, rapid, and contextualized insight through semantic analysis. Our products harness the power of unstructured data to provide organizations with deep discovery and new knowledge for optimal business decision making.
Our focus is on accuracy, timeliness, and contextual insight – all rare commodities in the world of electronic document and records monitoring and analysis.
Our AI multilingual platform is delivered through a software-as-a-service (SaaS) and platform-as-a-service (PaaS) model. The proprietary algorithms behind this platform have been imbued with linguistic and cultural specificity. Underneath the interface, Coginov Analytics uses proprietary algorithms leveraging semantic analysis to identify the context of concepts and entities.
Powered by our AI framework, Coginov’s analytics platform uses automated, industry-leading semantic analysis to learn from and bring out the context behind any topic within any document or information type.
Our context-aware analytics engine:
Many EDRM solutions stop at collecting data and monitoring for occurrences of specific keywords. The task of figuring out how to proceed with the data analysis, and understanding what strategic decisions are being suggested by the analysis, is usually left with the end-user, often resulting in analysis paralysis, lost time, and wasted money.
Coginov’s platform exists to solve this problem and catapult organizations’ data analysis prowess. By using NLP in combination with ML, our platform understands the context of a user query and provides a better, more tailored response to users’ questions.
In essence, our semantic analysis, using industry specific dictionaries and corralled by proprietary ML algorithms, creates a powerful way to identify the intent and meaning behind user queries, and to supply responses targeted to that context. This ensures that every user is quickly connected to the most relevant and helpful resources and insights, many of which would otherwise remain hidden within vast quantities of data.
Our platform’s ability to understand the context of the topics is a critical differentiator. Informed by the context of user queries, the platform goes well beyond simple keyword analysis and allows the user to instantly draw actionable conclusions. Coginov’s analytics platform focuses on precise, instantaneous analytics and in-depth insights. Our differentiators include:
Unique pre-validation of search results that ensures analysis is of the highest relevance
Browse through our site to find more information on the products that are most targeted to your needs or get in touch – we’d be happy to explore how Coginov can help your organization reach a new level of success.