Natural Language Processing company
Natural Language Processing services
Turn conversations into competitive advantage
What is Natural Language Processing?
Natural Language Processing gives you the power to process and understand massive volumes of unstructured text – from product reviews to tweets – and extract what truly matters: actionable insight into what your audience thinks, feels, and wants.
And it's booming: the NLP market is projected to hit $35 billion by 2026.
Why choose Devico for NLP services
High retention rate
96%
We go beyond the 80% industry norm with reliable, expert support.
Wide expert network
3000
Access to over 3000 engineers and AI experts.
Proven track record
500,000
Over 500,000 man-days successfully delivered.
Support
24/7
Highly experienced management team available around the clock.
Don't limit your data reach
The NLP industry grows at 21.82% annually, with over 2900 startups contributing to innovation among more than 18 000 companies
How does it work?
01
Start with real-world text
Raw language from reviews, chats, and documents becomes the foundation.
02
Extract what matters
Key patterns and signals are shaped into structured, usable features.
03
Apply intelligence
Advanced models interpret meaning, context, and intent – designed to the task.
04
Refine for precision
Performance is measured, gaps are closed, and accuracy improves.
05
Evolve with the language
COngoing monitoring ensures the system stays sharp, relevant, and aligned with change.
Industry-specific
NLP development
Healthcare
Healthcare NLP applications accounted for 20% of the market in 2024, reflecting its growing importance in AI-driven diagnostics and patient care.
NLP integration into daily operations brings a shift towards more intuitive and intelligent medical and diagnostic systems.
Use cases:
- Enabling better patient care and operational efficiency
- Analyzing unstructured medical data
- Extracting meaningful insights
Healthcare NLP applications accounted for 20% of the market in 2024, reflecting its growing importance in AI-driven diagnostics and patient care.
NLP integration into daily operations brings a shift towards more intuitive and intelligent medical and diagnostic systems.
Use cases:
- Enabling better patient care and operational efficiency
- Analyzing unstructured medical data
- Extracting meaningful insights
The finance industry is the natural promoter of the application of AI, more specifically, NLP for finance, in data automation.
NLP analysis has allowed lending institutions to recover between 70% and 95% of their uncollectible debts and increase their debt collection rates by 20%.
Use cases:
- Risk management
- Fraud detection
- Customer service automation
- Identifying trends and predicting market movements
Companies that integrate NLP for personalized content or responses into their business operations can significantly improve customer satisfaction and drive 40% more sales.
NLP is often used to analyze customer reviews and feedback, optimize product recommendations, and improve customer satisfaction.
Use cases:
- Personalized recommendations
- Sentiment analysis
- Chatbots for customer service
Manufacturing processes can be innovatively revamped with automating routine tasks, or developing personalized training modules. Such tailored solutions use the power of NLP to optimize workflows and improve overall efficiency.
47% of global manufacturers use NLP algorithms for this purpose to reduce operational costs.
Use cases:
- Improving supply chain management
- Predictive maintenance
- Quality control
Speak the language of your data
Understand customer intent, sentiment, and behavior at scale with powerful NLP solutions
Core NLP techniques
Technique
What it means
Goal
Usage
Data analysis
Extracting meaningful information from unstructured text data.
Identify patterns, trends, and insights from text data. Transform raw text data into a structured format suitable for further analysis by machine learning algorithms.
- Analyzing customer feedback
- Monitoring social media
- Processing legal documents
Text analysis
Evaluates and interprets emotions expressed in text data.
It classifies text as positive, negative, or neutral.
Understand the underlying sentiment behind user reviews, social media posts, or customer feedback.
Can significantly impact customer satisfaction.
- Customer service to gauge satisfaction
- Monitor brand reputation
- Analyze social media sentiments
Language translation
Converts text from one language to another using machine learning models.
Break down language barriers and ease communication.
- Real-time translation services
- Multilingual customer support
- Content localization
Speech recognition
Converts spoken language into text using machine learning algorithms.
Enable voice-activated interfaces, improve accessibility.
Some speech recognition systems can achieve word error rates as low as 5%.
- Virtual assistants like Siri and Alexa
- Transcription services
- Automated customer service
Chatbots
AI-powered programs that simulate human conversation to interact with users.
Automate customer service and provide instant responses.
- Customer support
- Deliver targeted marketing messages and recommendations based on user interactions
- Qualify leads and collect customer information through chatbot interactions
Get in touch
Drop us a line about your project and we will contact you within a business day
Our locations
New York
521 Fifth Ave, NY 10175
+1 805 491 9331London
9 Brighton Terrace, SW9 8DJ
+44 1922 214429Warsaw
Towarowa 28, 00-847
info@devico.ioLviv
Uhorska str. 14, 79034
info@devico.ioQuestions & answers
What problems can Natural Language Processing services actually solve for us?
From automating support to extracting insights from text, NLP services help make sense of language at scale – saving time, cutting costs, and unlocking new opportunities.
How do I know if NLP is the right fit for our product?
If you deal with unstructured text (emails, chats, reviews, documents), a Natural Language Processing company can likely turn that data into value.
Are NLP models reliable enough for production use?
Yes – when built and trained properly. As a solid Natural Language Processing company, we focuse on real-world accuracy, not just benchmarks.