Many companies suffer from the lack of an accurate and fast search engine that can handle complex data. Such information includes scientific datasets, candidates’ resumes, different inventory assets, etc. For the majority of businesses, it is costly enough and hardly possible to search among massive unstructured datasets.
Azati creates custom search engines from scratch for different companies and verticals. The team’s primary goal is to lower costs and simplify the development of advanced search algorithms.
We Build Search Engines Around
Structured data is data that has been somehow organized into a formatted repository, typically a database, so that its elements are addressable for more effective processing and analysis.
As structured information is best suited to automated processing, engineers build applications based on well-known search algorithms but improved by our engineers.
Typical computer science algorithms are less useful when working with unstructured data like plain text records, images, voice, sensor data, etc. The team created a pipeline that simplifies the processing of complex data: from initial data mining to natural language processing with sentiment analysis or image processing with computer vision.
The main goal of Azati is to turn unstructured information into structured or semi-structured data to make it suitable for traditional processing with statistical methods and known algorithms.
Semantics Is The Key
Sometimes during the processing of complex datasets, the main challenge becomes not to find a required entity but to understand what exactly the user expected to see as a result of a lookup. It means that the way an engine treats search query is also essential.
To improve search experience, Azati analyses not only the entered text but also the semantics and context of a query. It means a user may create much more complex search queries using natural language.
Search queries are processed with sophisticated natural language processing technologies, whose primary goal is to understand what stands behind words. The algorithms determine the main entities and parameters from the search query and analyze how these entities correlate with the initial dataset.
According to these correlations, ML models find out all the results that can be relevant to the query and filter them by the parameters provided by the user.
- Our team successfully created 9 enterprise-grade search engines in 2019 only
- Cutting-edge technologies help Azati to process almost all kinds of data
- Our applications speed up and simplify the business processes and complex workflows
- The team developed several templates to cut down general development costs
As healthcare abounds a considerable number of complex scientific datasets, it needs data scientists who accurately process biological data and creates tools that simplify this process for a regular user. Azati uses various computational methods, including machine learning, to eliminate chaos and turn the data into a competitive advantage.
One of the most challenging tasks of a recruitment domain is to select an employee who fully meets the requirements and job description. Search engines developed by Azati empower companies with automatic data collection from several sources, and accurate resume processing, which makes the screening process less stressful.
One of the main problems of the retail industry is a vast inventory, which should be constantly monitored and updated. The solutions Azati builds offer accurate and fast search among huge lists and provide intelligent recommendations if nothing is found. The user will never see the blank screen without any search results.
Featured Case Studies
Azati designed and developed a semantic search engine powered by machine learning. It extracts the actual meaning from the search query and looks for the most relevant results across huge scientific datasets.
Azati designed and developed an intelligent search engine for inventory search enhancing traditional search algorithms.
Azati designed and built up a recruitment platform for the staffing firm. The system comprises several interconnected modules microservices.
Data scientists developed a smart-matching algorithm that provides more consistent and precise search results for a widely known hiring platform.
Azati created Life Science Portal endowed with extensive search capabilities providing the functionality to search with multiple entry sequences across various nucleotide and peptide databases.
At Azati we created a complex solution for the local tradesman search (B2B and B2C) including the web portal, mobile application, and sophisticated search engine, powered by machine learning technologies.
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Azati creates various applications powered by advanced machine learning technologies and sophisticated models to simplify everyday work.Let’s discuss your idea