At nexocode, we specialize in custom natural language processing development services. We have a team of experienced machine learning developers who are well-versed in the latest NLP technologies and trends. We constantly strive to stay ahead of the curve and offer our clients the best possible NLP solutions. Some examples of the natural language processing projects that we have developed include:
We have extensive experience developing sentiment analysis tools that can help you understand the emotions and opinions expressed in text data. Understanding the sentiment in data can be used to monitor and analyze customer feedback, as well as to understand social media trends.
We can help you develop document processing solutions that can analyze text, provide semantic search or semantic reasoning, and automate the tedious and time-consuming tasks of manual data entry and processing. Our document processing tools can extract information from various document types, including PDFs, images, and scanned documents.
We can help you develop chatbots and virtual assistants to interact with your customers and provide them with the information they need. Chatbots and virtual assistants can be used to handle customer queries, solve support issues, provide product recommendations, and much more.
We can help you develop text classification and topic modeling solutions that automatically classify and organize your text data. Text classification is a process of automatically assigning texts to one or more predefined categories and can be used to sort emails, articles, customer reviews, and other types of text data.
We can help you develop entity recognition and entity extraction solutions to identify and extract entities from text data. Entity recognition is a process of identifying and classifying named entities in text and can be used for advanced text extraction and text mining tasks.
We can help you develop natural language generation solutions that can automatically generate text from data. Natural language generation is a process of generating texts from data and can be used to create reports, provide text summaries, descriptions, and other types of text data.
nexocode is a leading provider of software solutions based on natural language processing. If you are looking for an NLP solution that can support your business, our team of experts can help. We have a wide range of experience developing custom NLP solutions across industries. Contact us today to discuss your requirements.
Krzysztof Suwada
Data Science Expert
Dorota Owczarek
Design Thinking Facilitator & Product Lead
Oleksandr Zakharchuk
Machine Learning Expert & Advisor
Logistics and Supply Chain Management
NLP can benefit the logistics sector by automating the processing of invoices, customs records, bills of lading, and other documents. NLP solutions can help logistics companies automatically extract information from these documents and make better decisions by understanding the sentiment in customer feedback.
Healthcare, Pharma, and Life Sciences
NLP can be utilized to process patient records, clinical trial data, and medical research. NLP solutions may help healthcare organizations extract information from these sources automatically and produce new text documents, including reports, summaries, and explanations, by automating the extraction and generation of information
Banking, Financial Services, and Insurance
NLP has applications in many areas, including loan approvals, insurance claims handling, and consumer feedback processing. NLP solutions may assist banks, financial companies, and insurance organizations in extracting information from these sources automatically to identify fraud, improve customer service, and increase profits.
Retail, eCommerce, and Marketing
NLP can be used to process customer reviews, product descriptions, and social media conversations. Natural language processing solutions can help retail companies understand customer emotions through sentiment analysis, improve product descriptions, and offer recommendations. Machine learning can also help generate marketing content such as ads and brochures.
Manufacturing
Natural language processing can be used to process manufacturing data, customer feedback, warranty claims, and supplier contracts. NLP solutions can help manufacturers automate the processing of this data to improve quality control, reduce costs, increase profits and make better decisions by extracting critical information from various sources.
Energy and Telecommunications
NLP can be used to process energy data, customer feedback, and support requests. NLP solutions can help energy companies and telecommunications providers improve customer support, understand customer sentiment, and extract essential information from various sources. It can also provide solutions for automated document generation and to configure a network management system.
Natural language processing can be used to support your business in many ways. Some of the benefits of NLP solutions include:
To give you a better idea of the type of work we do, here are some case studies of the natural language processing projects that we have worked on:
Social Media Platform
Healthcare Sector
Travel Sector
At nexocode, we offer a wide range of natural language processing implementation services that can be tailored to your specific needs and requirements. nexocode's offering covers end-to-end NLP services from strategy, advisory, and consulting to implementation and ongoing production support.
We can help you assess the feasibility of using NLP to achieve your desired business outcomes and develop a roadmap for implementing NLP solutions. We organize AI Design Sprint workshops focused on NLP where you can unleash the artificial intelligence potential and create new value for your business.
NLP requires high-quality data to be effective. We can help you clean and prepare your unstructured data for NLP so that you can get the most out of your NLP solutions. Our Data Scientists will support you in conducting exploratory data analysis and advise on building a data strategy.
We offer a full range of natural language processing implementation services, from developing custom NLP deep learning models to deploying NLP solutions at scale. Our team of experienced machine learning developers will work closely with you to ensure that your project is completed on time and within budget.
nexocode provides full-cycle custom development services to help you build NLP solutions from scratch or improve your existing NLP system. We have a team of experienced product designers and developers who can lead product development in an agile way
We can help you integrate NLP solutions into your existing systems and workflows. We will work closely with you to understand your requirements and ensure that the integration is seamless and effective. In addition, the nexocode team can provide application maintenance and support for your solution.
Kickoff
Briefing
2 hours
Explain your business and share your pain points to gain insights into AI capabilities and an approach designed by our nexocode experts.
AI Design
Sprint
2 days
Identify a high-impact business problem and collaborate with nexocode experts to propose an AI solution.
Proof of AI
Development
4 – 12 weeks
Rapidly build an AI model that solves your problem and subsequently test machine learning algorithms on your datasets.
AI Application Deployment
in Production
3 – 9 months
Build automated pipelines, scale, and deploy your artificial intelligence app into production. Adjust algorithms to meet your desired benchmarks.
Natural language processing (NLP) is a branch of artificial intelligence and computer science that deals with the interaction between computers and human language. NLP technologies are used to build applications that can understand human language and respond in a way that is natural for humans. Natural language processing solutions are generally divided into natural language understanding (NLU) and natural language generation (NLG). For more information on NLP technology, head over to our Definitive Guide to Natural Language Processing.
There are many benefits to using NLP technologies in business, including:
Machine learning is a subfield of artificial intelligence that deals with the design and development of algorithms that can learn from data. NLP is a subfield of machine learning that deals with the design and development of algorithms that can understand and process human language. Machine learning algorithms can be used for a variety of tasks, including classification, regression, and image recognition. Natural language processing deals in particular with understanding, processing, and generation of the human language by machines.
Various NLP problems can be solved either with simpler statistical methods or more advanced deep learning models.
Huge companies such as Google, Facebook, Amazon, and Microsoft have been using NLP for a long time to improve their products and services. Many startups are also applying NLP technologies with great success. If you have a business that deals with customer service, data entry, text processing, or document generation, then NLP can help you save time and money.
There is no guarantee, however, that a custom NLP software will get this expected value or the total cost will not be too high to handle. That is why a detailed planning phase and an iterative approach are crucial in every AI-based project. Only in this way will you be able to predict the cost, income, and break-even points of your development. There are ways to reduce the risk of not getting value from solutions that use AI. nexocode's approach is based on a deep understanding of the needs of the projects and the possibilities of current AI technologies coupled with the iterative approach. Our project methodology focuses on delivering value as early as possible and starting small with AI Proof of Concept development.
You can find out more about how to turn AI into a profitable investment in our article on theROI of AI. Our team will help you leverage the latest AI tools and methodologies to create practical data-driven applications that deliver real business value.
There is no one-size-fits-all answer to this question. The amount of data required for a natural language processing project will depend on the type of task you are trying to accomplish, the complexity of the task, and the available resources. In general, however, it is advisable to have as much data as possible when working on deep learning projects, as more data will allow the algorithm to learn and improve its performance.
Our Data Scientists are experienced in providing preliminary Data Quality Audits and in preparing a dedicated data collection strategy for our clients.
We are experienced in working with a wide variety of data sources and formats. We can help you clean and prepare your data for natural language processing. Our team can also help you not only with preprocessing or data annotation but also with designing and implementing a custom data collection strategy tailored to your specific needs.
Transfer learning, a deep learning subset of advanced machine learning methods, which was introduced by researchers in 2019, drastically lowers the amount of data required for machine learning by pre-training models on other data. The discovery of this NLP technology has had a major impact on reducing the cost of building practical NLP systems. Plenty of open-source NLP libraries are also available, which can further reduce development costs.
The cost of a natural language processing project will also depend on the specific requirements and the size and complexity of the project. A detailed planning phase and an iterative approach are crucial in every AI-based project.
Please contact us to discuss your specific project needs and get a price quote. Our team will work with you to develop a custom solution that fits your budget and meets your requirements.
Python is the most popular programming language for natural language processing. However, many other languages can be used for NLP development, such as R, C++, and Julia. The choice of language will depend on the specific requirements of the project.
When it comes to frameworks and libraries focused on NLP and building deep learning language models, TensorFlow, PyTorch, Keras, and SpaCy are the most popular. We can enrich the performance of human language processing systems by leveraging existing natural language tool kits to identify concepts, keywords, categories, semantics, and emotions and to perform text classification, entity extraction, relationship extraction, named entity recognition (NER), sentiment analysis, and summarization.
Integrating an NLP solution with internal systems will vary depending on the project's specific requirements. However, it is advisable to use APIs or web services to avoid any compatibility issues.
Our software engineers and DevOps team will help you build a scalable, integrated solution for speech recognition, machine translation, text summarization, keyword extraction, or named entity recognition that is seamlessly synced with your existing systems and solutions.
Thinking about starting an NLP project, but not sure where to begin? We can help.
Whichever industry you are in, if your business involves text data in any way, nexocode's natural language processing services can help you get more value from that data. We have a team of experienced data scientists and software engineers who are experts in the field of natural language processing. We can help you with all aspects of your project, from training data collection strategy and implementing an MVP machine learning model to building robust NLP solutions at scale.
The first step is to contact us and schedule a consultation. We will discuss your specific needs and requirements and help you decide if natural language processing is the right solution for you. We will also provide you with a detailed proposal outlining our approach and the expected deliverables.
