NLP Service Provider

Harness the power of natural language processing for fact extraction, speech recognition, sentiment analysis, and much more with Serokell's AI expert services.

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What is NLP?

Natural language processing (NLP) is a field of artificial intelligence that allows computational systems to understand human language.

NLP combines deep learning models with computational linguistics. Using these technologies, computers are able to process written or spoken language in the text or audio format and recognize what is being said or written, including the intentions and feelings.

Benefits of NLP

Better data analysis

Natural language processing allows AI to quickly analyze unstructured data such as documents, emails, or surveys and extract meaningful information out of it.

Improved operations

NLP solutions free up the employees from manual processing of documents. Your staff can use their energy for more creative tasks that grow your business.

Reduced costs

By streamlining your operations with AI, you reduce costs. For example, NLP is the main technology for chatbots and digital assistants. This allows you to have less people involved in customer service while increasing customer satisfaction.

Focus on priorities

Once your employees are empowered with NLP-based assistance, they can focus on the vital issues of your business. Valuable insights obtained by means of NLP enable them to quickly react to users’ expectations and market changes.

Competitor analysis

Collections of mentions, product announcements, and positioning of your competition are available to you without effort. Alternatively, you can integrate NLP-driven competition analysis into the SaaS solution for your customers.

Natural language processing services

Accelerate and optimize your business operations with advanced AI solutions by Serokell:

Data extraction

Whenever you need information about a specific subject across bodies of text, data extraction tools will perform this task in a matter of seconds.

Topic analysis

By identifying recurring topics in texts, you can gain valuable insights from your customer feedback. It is also an essential tool in scientific research where big amounts of text needs to be analyzed.

Text generalization and summarization

Volumes of information generated daily makes it impossible for humans to process and analyze. Text generalization and summarization provides you with a quick overview of the most important issues.

Text transcription

From daily meeting notes to large video conference records, natural language processing automates the transcription of speech into text. This facilitates further work with the written information, suc as automatic creation of word documents or subtitle generation for audio and video files.

Content categorization

The variety of content produced in the course of daily operations needs to be classified for easy management. Categorization allows you to assign predefined tags and labels to content. Among other things, this can be used for automating routine tasks such as filling out forms.

Entity recognition

By identifying specific entities in texts, such as names of people, companies, and products, places, quantities, values, etc., you can monitor the mentions of your brand, organization, or competitors.

Automation of customer service

NLP-based chatbots and digital assistants reduce the costs of customer service while enhancing customer experience. You can address your clients’ needs and onboard prospects more quickly and efficiently.

NLP projects we
have worked on

Audience segmentation

We provide automated audience segmentation based on NLP technologies for an innovative mobile advertising platform. The tool can identify desired audience segments based on keyword analysis and determine optimal targeting without human involvement.

Active learning for NER

Named entity recognition, or NER, is one of the most popular tasks in NLP. It involves finding named entities in texts and is used to recognize mentions of companies, people, brands, and places. We have introduced a comprehensive framework in which several active learning techniques and transformer-based classifiers have been implemented to achieve better model performance.

Noun compounds

To improve the quality of written text analysis, we have trained a new model which classifies noun phrases according to their meaning. This novel technique outperformed previous solutions and provides AI classifiers with a better understanding of compound nouns.

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Natural language processing toolkit

Serokell specialists have in-depth knowledge of Python – the programming language used for NLP tasks. Thanks to the extensive experience with libraries such as NLTK, TextBlob, Gensim, CoreNLP, etc., we provide the best solution to your problem.

Deep learning

We use deep learning models based on convolutional neural networks (CNNs), time-delay networks (TDNNs), recurrent neural networks (RNNs), etc. Our R&D team will evaluate your requirements to provide the most appropriate model based on the business goals.

Our tech stack

Automate your business with NLP technologies

Automate your business with NLP technologies

Speech recognition

Speech recognition, also referred to as speech-to-text or voice-to-text, is the process of converting speech data into text. Improve your apps with chatbots and voice assistants with this advanced technology.

Sentiment analysis

Sentiment analysis identifies emotions and attitudes in texts. Improve your reputation by identifying positive and negative trends in your customer feedback and taking timely action.


Disambiguation is the semantic analysis of words with several meanings. Improve the performance of your chatbots by determining the meaning of the words that make the most sense for the context.

Data cleansing

NLP-based data cleansing removes irrelevant information ("noise") from datasets. Analyze your data to understand your business better. Make well-informed strategic decisions.

Natural language generation

Natural language generation is the process of converting structured data into human speech. Create meaningful written and voice texts in no time to enhance internal and external communications.

Speech recognition, also referred to as speech-to-text or voice-to-text, is the process of converting speech data into text. Improve your apps with chatbots and voice assistants with this advanced technology.

Why choose us for NLP development


Serokell has a highly professional team of developers with proven expertise in machine learning – the key process behind natural language processing.

Custom approach

Our experts address each case individually. We always start from in-depth research and analysis to offer the most effective and scalable solutions for your business.


Established in 2015, Serokell has successfully completed numerous complex projects in artificial intelligence.

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How can natural language processing help my business?

NLP frees up employees by automating routine tasks. It reduces bias and human error in document processing. In addition, natural language processing is effectively used in AI assistants that help answer customer queries immediately, increasing customer satisfaction.

What are the examples of natural language processing?

Real-life examples of NLP use include email filters, virtual assistants and smart speakers, chatbots, search engines, machine translation, and autocorrection. With a wide range of applications, NLP keeps evolving to include monitoring of brand sentiment, customer feedback analysis, and natural language generation.

How do NLP algorithms work?

Natural language processing algorithms are typically ML algorithms. Instead of learning a bunch of rules, NLP automatically learns patterns. Each NLP algorithm handles specific tasks such as stemming (identifying the root), keywords extraction, tokenization (breaking down the text into sentences and phrases), or sentiment analysis.

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