Yes, we care. We aim to meet your needs, whatever they are. Combining best-of-breed text mining technologies with human expertise enables us to know the correct answers and solutions to essential challenges. Instead of gathering and processing data you can focus all your energy on analysis and insight.
Unmatchable quality
We can outperform anyone in the industry by reaching 90%-99% high precision and quality of results, achievable usually through manual work.
Optimal approach
It’s the pairing of humans and machines that yields the best results. We use knowledgeable analysts to train the technology with your own data sets.
Advanced flexibility
Identrics flexible integration framework for data processing and semantic analysis allows us to design and combine together diverse technologies.
Our Most Popular Solutions
Entity Extraction
Content categorization
Automated recommendations
Entity Extraction
The extraction and classification of entities in your text data facilitates search, provides new information and infers new knowledge from existing facts. We automatically find mentions of entities such as persons, organisations, brands, locations, events, e-mails, etc.
Extracting information from unstructured data is a staggering task, considering the complexity of natural languages. Identrics’ personalized entity extraction models guarantee the highest quality available on the market. Our models can learn fast to identify all textual mentions of entities of interest from a pre-defined data set. We supervise how the named-entity recognition technology works and give it regular feedback to improve its efficiency.
Who we help:
E-businessExtract product and service features from unstructured descriptions
Risk and ComplianceExtract critical facts related to KYC, AML. Analyze research for patent law, legal discovery, and compliance
Government and public sector Organise documentation to improve search and findability. Identify specific person for government security and fraud detection.
Media and publishing Provide targeted search for content publishers and recommendation engines
A case study: A global financial data and news publisher had a request for processing a large set of news articles to extract entities which were reported to have been involved in a specific criminal activity as well as the phase of the legal process and the crime’s monetary value. Our solution was to use semantic technologies based on entity-related context and specific rules for relevancy prediction based on the project criteria. NER and entity classification, both based on machine learning, came in handy – we’ve trained a classifier to identify the entities which the client was interested in.
Content categorization
Having tonnes of information isnt much good if you cannot do anything with it. We let you turn all the information you have in an organized, streamlined and above all else, useful resource. Classifying your content and products into categories helps users to easily search and navigate within a website or application. We utilise a comprehensive list of taxonomies to categorise text content into definitive tags. Taxonomy classification facilitates focussed research, recommendations, knowledge management, text mining, information retrieval, content summary and cognitive filtering.
Who we help:
E-business, news agencies, content curators, directories Improve browsing and findability of related content on your platform or database.
Marketing and salesSpeed up the process of research and analysis of tags and keywords used by competitors.
Commercial enterprises Make sure content of all types - documents, reports, manuals, training material, performance data and metrics - is both findable and shareable throughout the organization.
Government, academic institutions, law practitioners Handle piles of unstructured data/text much easier by standardizing it by categories.
A case study: A media outlet has requested us to update its taxonomy that hasn’t been changed for years and already needed a revision, such as adding new topics, industries and countries. The news organization wanted to serve up the most relevant content to its audiences, yet it was too time-consuming and expensive for them to go through all the bulky archives by hand. In contrast, our automation can apply any changes to tagged articles as fast as possible. Identrics applied the new and upgraded taxonomy on millions of articles and did a job that no human was able to do.
Automated recommendations
Recommending articles for further reading has become extremely important to content providers looking to maintain interest and engagement after an initial visit to a website. Most online publishers have a selection called “More on this topic” showing related headlines next to an opened article. Traditionally, all that picking and linking of additional content is made by the editorial staff by hand. This cumbersome task takes a lot of time which can be spent in a more creative way once the organisation gets an intelligent engine that will automatically generate recommendations.
NLP can match human affinities not only with content but also with brands, products, services to produce relevant recommendations. When we have millions of items, a technology has no trouble finding documents, articles, videos, goods or deals of interest while a human will. On top of that, a technology is not biased - its choice will not be influenced by a particular mood or opinion but determined by statistics.
Who we help:
Media and publishingInstead of going through endless archives, use your energy to cover the next big story that readers should know about.
E-commerce and online storesBoost sales by offering product recommendations based on solid data.
Airline and travel companiesEnhance your CRM campaigns by targeting the right promotion to the right audience.
Financial providersFind the information you need effortlessly with an improved search engine.
A case study:A leading e-commerce company has asked Identrics to create automated product suggestions for its website users. The retailer wanted to serve better its clients while shopping and offer them the right selection of products. We used a series of sophisticated rules for relevance together with machine learning technologies to show additional products to customers. New buyers saw bestsellers and products proven to engage, while existing customers viewed suggestions tailored to their purchase history.
We'd love to talk to you
If you are interested in our solutions or need consultation, do not hesitate to contact us. We like the human touch!
