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Natural Language Processing Application Development

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Unlock unparalleled insights from your data, provide better client assistance, and streamline your internal processes: pick Devox to take on natural language processing development that transforms complex language data into actionable intelligence.

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How Can they Help My Business?

What are Natural Language Processing Application and How Can they Help My Business?

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through the natural language. NLP applications, therefore, can maintain a dialogue: those are, for instance, well-renowned solutions like Bard or ChatGPT.

NLP as a concept enables computers to understand, interpret, and produce human language in a valuable way. Thanks to leveraging this new brand of artificial intelligence, machines can analyze, understand, and derive meaning from human language in a smart and useful manner.

Services We Provide

Natural Language Processing Application Services We Provide

Natural language processing solutions work with texts in different ways: whether you need a text processing or translation solution, an enhanced search engine, or a customer service AI chatbot, Devox can work with your project. See what we can develop.

  • Custom NLP software development

    Whether you’d like to get an extended conversational AI application like ChatGPT or another custom tool that will help your business leverage natural language processing, Devox can offer detailed consulting and a tailored solution. Be it a conversational AI chatbot service or a more scaled system, you can voice the requirements to us.

  • Chatbots and Virtual Assistants

    Devox can develop conversational agents that can understand and respond to user queries in natural language: these are AI chatbots for customer service that provide support, information retrieval, interaction capabilities, and facilitate transactions. Ideal for improving customer engagement, streamlining operations, and offering 24/7 support without the need for extensive human resources.

  • Text Analytics and Categorization

    We can create applications that analyze text data from social media, reviews, customer feedback, and other sources, categorizing and tagging content based on its subject matter. You’ll determine sentiments, opinions, trends, and key themes, understanding your audience’s perceptions and responding to them quicker and better – along with improving content management.

  • Language Translation Applications

    Building applications that can accurately translate text or spoken language from one language to another, facilitating global communication and content localization. Achieve accurate and context-aware translations, making them invaluable for global operations and breaking down language barriers, reaching a wider audience.

  • Semantic Search Engines

    Creating advanced search systems that go beyond keyword matching to understand the intent and contextual meaning behind search queries. The combined potential of NLP and semantic technology allows search engines to deliver more relevant and precise results, improving user experience and information retrieval accuracy. Ideal for businesses aiming to enhance their data discovery, customer support, and content navigation capabilities.

Development Process

Our Natural Language Processing Application Development Process

The development of natural language processing is a part of classic SDLC. See how Devox will be making your solution from scratch in detail.

01.

01. Defining Objectives and Requirements

Together with you, our team clearly defines what the application aims to achieve: whether it’s enhancing customer service, automating content analysis, or salvaging insights from text data you’re after, we identify these as key requirements. We discuss the languages supported, the volume of data to be processed, as well as any industry-specific needs, including organizational (team size and sprints) and technical (languages and frameworks) moments as well.

02.

02. Data Collection and Preparation

Our developers gather textual data relevant to the application’s objectives. This can include public datasets, customer feedback, social media posts, etc. We then clean the data to remove noise, such as irrelevant information, errors, or duplicates, ensuring the quality of the data for analysis. Data annotation is what follows: for supervised learning models, we label or annotate the data to provide examples for the model to learn from.

03.

03. Model Selection and Training

Now, we pick the appropriate NLP algorithms and techniques, such as machine learning models, deep learning architectures (e.g., RNNs, CNNs, Transformers), or rule-based systems, based on the application’s requirements. With these tools, or engineers train the model using the prepared dataset, adjusting parameters and structures to improve accuracy and performance.

04.

04. Development and Integration

We develop the application, integrating the NLP model with the user interface and backend systems. During this process, we programm the application logic and design the user experience. We then integrate the NLP application with existing business systems, such as customer relationship management (CRM) systems, data warehouses, or web platforms.

05.

05. Testing and Evaluation

Once the application is done, it’s time to conduct thorough testing, including unit tests, integration tests, and user acceptance testing (UAT), to identify and fix bugs or issues. Finally, we evaluate the application’s performance in terms of accuracy, speed, and scalability, using metrics relevant to the application, like precision, recall, and F1 score for classification tasks.

06.

06. Deployment

We deploy the application in a controlled environment or to a limited user base to monitor its performance and collect feedback. Full deployment is just coming: once confident in its stability and performance, fully deploy the application for all users.

07.

07. Maintenance and Support

We continuously monitor the live application for any issues or areas for improvement, regularly updating it to refine algorithms, add new features, and improve user experience based on feedback and technological advancements.

  • 01. Defining Objectives and Requirements

  • 02. Data Collection and Preparation

  • 03. Model Selection and Training

  • 04. Development and Integration

  • 05. Testing and Evaluation

  • 06. Deployment

  • 07. Maintenance and Support

Key Functionalities

Key Functionalities to Add to Your Custom Natural Language Processing Application System

01

Information Extraction and Summarization

Extract specific information like names, places, dates, and other relevant data from unstructured text, enabling efficient data processing and analysis. We’ll create tools that automatically generate concise summaries of long documents, articles, or reports, saving your staff’s time and making information consumption easier.

02

Content Categorization and Tagging

Automatically categorizing and tagging content based on its subject matter, improving content management, discoverability, and organization.

03

Natural Language Understanding (NLU)

This functionality allows applications to comprehend and interpret human language, including the intent behind texts or spoken words. It enables machines to understand queries, instructions, or any text input in a way that is meaningful, considering context, slang, idioms, and even errors in the input language.

04

Natural Language Generation (NLG)

NLG is the process by which computers generate narrative text from a dataset, providing the ability to articulate insights, summaries, or responses in a human-like manner. This functionality is crucial for report generation, automated content creation, and providing users with information in a concise and understandable format.

05

Named Entity Recognition (NER)

Identifying and classifying key elements in text into predefined categories, such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, and percentages.

Benefits

Benefits of Implementing Natural Language Processing Application

Natural language processing software development will transform your user experience and help you cater to your user better. Regardless of the exact solution, it can bring you several tangible advantages: see what those are.

  • Improve Customer Service

    NLP-powered chatbots and virtual assistants can provide instant, 24/7 customer support, handling inquiries, solving problems, and even processing transactions without human intervention, increasing customer satisfaction and loyalty.

  • Streamline Content Creation

    Automate content creation for reports, summaries, and even news articles, saving time and resources while maintaining the high-quality output of your media. Natural language processing will cater to your style and suggest relevant content ideas, bringing a fresh perspective while making it easier for your copywriting team.

  • Personalize Content on Advanced Level

    Capture more diverse users and retain them like a pro: NLP can tailor content, recommendations, and marketing messages to individual users based on their preferences, behaviors, and interaction history. Watch your conversion rates grow without deepening into SEO nuances.

  • Analyze Sentiments Accurately

    Understanding the nuances of human language lets NLP applications accurately gauge customer sentiment from text data. You’ll catch critical feedback on customer attitudes towards products, services, and brand overall swiftly, having a comprehensive picture of your business’ portrayal.

  • Language and Voice Processing

    NLP enables the development of applications that support multiple languages and dialects, breaking down communication barriers and expanding market reach. Voice-activated systems also offer an intuitive way for users to interact with technology.

  • Leverage Intelligent Search Functions

    Improve user experience and information retrieval efficiency: semantic search capabilities powered by NLP understand the context and intent behind search queries, providing more accurate and relevant search results, providing user with smoother online experience.

Case Studies

Our Latest Works

SwissMentor
  • Backend
  • Frontend
  • Cloud
  • E-Learning

Comprehensive Learning Management System

SwissMentor is a learning management system (LMS). It’s the software for managing all sides of the educational process: the main features include course management, invoicing, room management, document management, and e-learning.

Additional Info

Core Tech:
  • .NET Core
  • PostgreSQL
  • Angular
  • Docker
  • Kubernetes
  • Azure
  • SCORM
Country:

Switzerland Switzerland

Joynd
  • Frontend
  • Backend
  • Cloud & DevOps

Streamlining HR tools for efficiency

Joynd is a system that integrates different HR tools into one platform, allowing client companies to leverage the potential of different software within a single platform. The software connects companies who wish to use HR software from one side and such technical providers from the other side. It allows for a quick and effective integration with multiple suppliers.

Additional Info

Core Tech:
  • Angular
  • NgRx
  • RxJS
  • Tailwind CSS
  • .NET Core
  • PostgreSQL
  • AWS
  • Docker
Country:

USA USA

Juriba
  • Backend
  • Frontend
  • Cloud
  • DevOps & Infrastructure

Enterprise Digital Workplace Management Platform

Juriba is a broad system providing end-to-end automation and smart workflows required to manage large IT projects. With advanced features like seamless integration with existing tools, smart automation and data-driven dashboards and reports, it’s specifically tailored to digital solutions production.

Additional Info

Core Tech:
  • .NET 6
  • MS SQL
  • Redis
  • Angular
  • NgRx
  • RxJS
  • Kubernetes
  • Elasticsearch
Country:

United Kingdom United Kingdom

and over 200 our featured partners and clients

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Awards & Certifications

Industry Contribution Awards & Certifications

Check Devox Software Awards on rating & review platforms among top software development companies and Certifications our team members holds.

  • Awards
  • Certifications
  • UpWork

    UpWork

  • Clutch

    Clutch

  • The Manifest

    The Manifest

  • DesignRush

    DesignRush

  • MC.today

    MC.today

  • Clutch

    Clutch

  • Clutch

    Clutch

  • AppFutura

    AppFutura

  • Clutch

    Clutch

  • GoodFirms

    GoodFirms

  • DesignRush

    DesignRush

  • UpWork

    UpWork

  • Professional Scrum Master™ II (PSM II)

    Professional Scrum Master™ II (PSM II)

  • Professional Scrum Product Owner™ I (PSPO I)

    Professional Scrum Product Owner™ I (PSPO I)

  • ITIL v.3 Foundation Certificate in IT Service Management

    ITIL v.3 Foundation Certificate in IT Service Management

  • ITSMS Auditor/Lead Auditor of ISO Standard 20000

    ITSMS Auditor/Lead Auditor of ISO Standard 20000

  • Microsoft Certified: DevOps Engineer Expert

    Microsoft Certified: DevOps Engineer Expert

  • Microsoft Certified: Azure Administrator Associate

    Microsoft Certified: Azure Administrator Associate

  • Quality Assurance ISTQB Foundation Level

    Quality Assurance ISTQB Foundation Level

  • Microsoft Certified Solution Develop (MCSD)

    Microsoft Certified Solution Develop (MCSD)

  • Java Development Certified Professional

    Java Development Certified Professional

  • JavaScript Developer Certificate – W3Schools

    JavaScript Developer Certificate – W3Schools

  • Certified Artificial Intelligence Scientist (CAIS)

    Certified Artificial Intelligence Scientist (CAIS)

  • Oracle Database SQL Certified Associate

    Oracle Database SQL Certified Associate

Testimonials

Testimonials

Estonia

The solutions they’re providing is helping our business run more smoothly. We’ve been able to make quick developments with them, meeting our product vision within the timeline we set up. Listen to them because they can give strong advice about how to build good products.

Carl-Fredrik Linné
Tech Lead at CURE Media
Darrin Lipscomb
United States

We are a software startup and using Devox allowed us to get an MVP to market faster and less cost than trying to build and fund an R&D team initially. Communication was excellent with Devox. This is a top notch firm.

Darrin Lipscomb
CEO, Founder at Ferretly
Daniel Bertuccio
Australia

Their level of understanding, detail, and work ethic was great. We had 2 designers, 2 developers, PM and QA specialist. I am extremely satisfied with the end deliverables. Devox Software was always on time during the process.

Daniel Bertuccio
Marketing Manager at Eurolinx
Trent Allan
Australia

We get great satisfaction working with them. They help us produce a product we’re happy with as co-founders. The feedback we got from customers was really great, too. Customers get what we do and we feel like we’re really reaching our target market.

Trent Allan
CTO, Co-founder at Active Place
United Kingdom

I’m blown up with the level of professionalism that’s been shown, as well as the welcoming nature and the social aspects. Devox Software is really on the ball technically.

Andy Morrey
Managing Director at Magma Trading
Vadim Ivanenko
Switzerland

Great job! We met the deadlines and brought happiness to our customers. Communication was perfect. Quick response. No problems with anything during the project. Their experienced team and perfect communication offer the best mix of quality and rates.

Vadim Ivanenko
Jason_Leffakis
United States

The project continues to be a success. As an early-stage company, we're continuously iterating to find product success. Devox has been quick and effective at iterating alongside us. I'm happy with the team, their responsiveness, and their output.

Jason Leffakis
Founder, CEO at Function4
John Boman
Sweden

We hired the Devox team for a complicated (unusual interaction) UX/UI assignment. The team managed the project well both for initial time estimates and also weekly follow-ups throughout delivery. Overall, efficient work with a nice professional team.

John Boman
Product Manager at Lexplore
Tomas Pataky
Canada

Their intuition about the product and their willingness to try new approaches and show them to our team as alternatives to our set course were impressive. The Devox team makes it incredibly easy to work with, and their ability to manage our team and set expectations was outstanding.

Tamas Pataky
Head of Product at Stromcore
Stan Sadokov
Estonia

Devox is a team of exepctional talent and responsible executives. All of the talent we outstaffed from the company were experts in their fields and delivered quality work. They also take full ownership to what they deliver to you. If you work with Devox you will get actual results and you can rest assured that the result will procude value.

Stan Sadokov
Product Lead at Multilogin
Mark Lamb
United Kingdom

The work that the team has done on our project has been nothing short of incredible – it has surpassed all expectations I had and really is something I could only have dreamt of finding. Team is hard working, dedicated, personable and passionate. I have worked with people literally all over the world both in business and as freelancer, and people from Devox Software are 1 in a million.

Mark Lamb
Technical Director at M3 Network Limited
FAQ

FAQ

  • How has NLP development evolved in recent years?

    Recent developments in NLP have been driven by advances in machine learning and deep learning, particularly with the introduction of transformer models like BERT and GPT. These models have significantly improved the understanding and generation of natural language by computers, enabling more complex and nuanced interactions.

    There’s been a shift towards models that can learn from fewer examples, adapt to different languages more easily, and process information in a more context-aware manner, enhancing the applicability of NLP across various domains and languages.

  • Can NLP applications adapt to industry-specific jargon?

    Yes, NLP applications can be tailored to understand and process industry-specific jargon by training on specialized datasets containing domain-specific language and terminology. This training enables the applications to recognize and interpret the unique vocabulary and expressions used in industries such as legal, medical, or technical fields. Developers often collaborate with domain experts to curate and annotate these datasets, ensuring the models accurately reflect the language and nuances of the specific industry.

  • What programming languages are commonly used in NLP application development?

    Thanks to its simplicity and the extensive availability of libraries such as NLTK, spaCy, and TensorFlow, Python stays the most popular programming language for NLP application development. However, natural language processing with Python solutions is not the only way to make such an application, and developers also use other languages like Java and R, especially in enterprise environments: Java offers robustness and scalability for large-scale NLP systems, while R is favored for statistical analysis and data visualization in research contexts. The language choice is made based on the specific needs of the project, including performance requirements, existing infrastructure, and developer expertise.

  • How do NLP applications interact with users in real-time?

    NLP applications interact with users through chatbots, virtual assistants, and voice-activated systems. These systems use natural language understanding (NLU) to comprehend user queries and intents and natural language generation (NLG) to create responses that mimic human conversation. Real-time processing is facilitated by advanced algorithms and cloud computing, allowing for scalable and efficient user interactions. This enables applications to provide instant feedback, answer questions, and perform tasks based on user commands, creating a seamless and intuitive user experience.

  • What are the main challenges in developing NLP applications?

    Developing applications for natural language processing services involves challenges such as understanding context and ambiguity in language, handling diverse languages and dialects, and ensuring privacy and ethical use of data. Context and ambiguity require sophisticated models that can discern subtle nuances in language. Supporting multiple languages and dialects demands extensive datasets and sometimes language-specific models.

    Additionally, developers must navigate data privacy laws and ethical considerations, especially when processing sensitive or personal information, ensuring transparency and user control over their data.

  • How do NLP applications ensure accuracy in language translation?

    NLP applications improve language translation accuracy by using neural machine translation (NMT) models that leverage deep learning to understand the context and semantics of the source and target languages. These models are trained on large corpora of bilingual text data, enabling them to capture idiomatic expressions and subtle linguistic nuances. Continuous learning from new data and user feedback helps refine these models over time. Moreover, some applications incorporate human-in-the-loop processes to verify and correct translations, ensuring high levels of accuracy.

  • What future developments are expected in NLP technology?

    Future developments in NLP technology are anticipated to focus on improving model efficiency, expanding multilingual support, enhancing understanding of context and nuance, and advancing ethical AI practices.

    There is ongoing research into making models more lightweight and efficient without sacrificing performance, enabling their deployment on a wider range of devices. Efforts to create models that can seamlessly handle multiple languages simultaneously are expected to break down language barriers further. Additionally, there is a strong focus on developing models that better grasp context, irony, and humor in text.

    Ethical AI practices will also be a key consideration, ensuring that NLP technologies are developed and used responsibly, emphasizing privacy, fairness, and transparency.

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