Natural language processing analyses and understands human language for various applications
Natural Language Processing (NLP) is an AI-driven technology
that enables machines to understand, analyze, and interpret human
language. By leveraging advanced NLP algorithms, businesses can
extract insights from text data, power chatbots, perform sentiment
analysis, and enhance intelligent language understanding for smarter
human-computer interaction.
Innverse helps private and public natural language processing leaders make
better, more affordable, and more accessible for millions of people around the world.
Unlock the value of your data with Natural language processing software
Machine learning projects often involve uncertainty, technical complexity, and significant execution
risks. Without the right in-house AI expertise, it can be challenging to successfully plan, develop, and
scale a custom AI solution that delivers real business value.
We have delivered more than 100 custom AI solutions across 20 countries worldwide and developed the
national AI
strategy for the Government of Estonia. With proven experience in AI development services and
enterprise AI implementation, our team has the expertise to confidently support and execute your AI
project end-to-end.
Stop Processing Speech or Text Manually
services
One of the primary advantages of machine learning is its ability to analyze and process unstructured
data,
including text, speech, and documents. Unlike traditional keyword-based searches or manual audio
transcription, machine learning can efficiently extract meaningful insights, uncover patterns, and
transform raw data into actionable intelligence. This capability enables businesses to make faster,
more
accurate data-driven decisions and improve operational efficiency.
At Innverse, we develop advanced Natural Language Processing (NLP) solutions designed to
unlock the
full value of your data. Our AI-powered systems automate repetitive tasks, enhance understanding of
textual and
audio content, and deliver actionable insights. By leveraging cutting-edge NLP algorithms and
machine learning
techniques, we empower organizations to streamline workflows, gain strategic insights, and drive
smarter business
outcomes.
We provide natural language processing solution
Data labeling
Data Labelling involves adding tags or annotations for machine learning.
Data architecture
Data architecture designs the structure and flow of information systems.
AI strategy
AI strategy outlines plans for implementing artificial intelligence initiatives effectively.
Piloting
Piloting involves testing small-scale implementations to assess feasibility and effectiveness.
Scaling
Scaling refers to expanding and optimising systems or operations for growth.
NLOps
Natural Language Processing, involves analysing and understanding language data.
Data collection
Data collection entails gathering information for analysis, often from diverse sources.
App development
App development involves creating software applications for various platforms and devices.
It means that we are with you from the start to the finish of the final
solution
From validating ideas on the business side to creating a strategy that is based on them. Making sure
everything is ready from the data side from quality, quantity, engineering and scalability.
We set up all the necessary MLOps infrastructure for initial pilots and scale successful pilots.
Of course, we develop the actual AI models producing the desired output and the supporting
applications to exploit the output of those models.
AI for business: Reinvent what's possible
AI is rapidly accelerating into a global mega-trend, transforming industries,
reshaping businesses, and redefining how we live and work. Organizations that invest in a strong
data and AI foundation are positioned to lead this new era of digital innovation,
enabling them to reinvent processes, enhance decision-making, and achieve unprecedented levels of
performance, efficiency, and scalability.
At Accenture, companies are guided from AI interest to actionable strategies that deliver measurable
business value. Through responsible AI adoption and
clear business-use cases, organizations receive end-to-end support—preparing their data, teams, and
workflows for AI-driven transformation. With a secure,
cloud-first digital core, businesses can unlock continuous reinvention, improved resilience, and
sustainable growth powered by advanced analytics, automation, and enterprise AI solutions.
Artificial Intelligence
A new era of generative AI for everyone
In today’s fast-evolving digital landscape, generative AI is
reshaping how businesses innovate, operate, and grow. At INNVERSE, we believe we are entering a
new era where generative AI is no longer limited to tech giants
or research labs—it is becoming an accessible, practical, and transformative resource for
everyone.
While it is easy for us to read a sentence or a paragraph and figure out whether
it’s about ordering pizza, the weather, or the news, doing so on a large scale can be very
time-consuming.
AI-based natural language understanding (NLU) solutions allow machines to perform these tasks at a speed
that is unmatched by humans. This allows us to classify entire documents, divide them into sections by
topic, understand the user’s intent in a conversation, or extract pieces of information from long texts.
These features serve as the foundation for conversational interfaces and allow for
use cases like topic-based news article filtering, information extraction from CVs, and spam email
detection.
Sentiment analysis
Languages are very nuanced, so while some of the information is factual, like a
judgement that the restaurant’s food was bad, other parts are emotive, like the man’s outrage about the
food’s quality.
Machines are generally not very good at reading emotions, but with the aid of AI, they can pick up cues
that indicate the sentiment attached to a segment of text, showing whether the content is happy, sad, or
evokes any other sentiment the model is trained to recognize.
This allows our clients to better understand their customer feedback, adjust
chatbot responses, and react to prevailing sentiments regarding specific topics reflected in the
comments. It has also been used to understand sentiment concerning specific topics in the media and on
social media. In this case, NLU and sentiment analysis are used in tandem to recognize topics of
interest and subsequently interpret sentiments about them.
Speech recognition
Speech recognition allows a machine to understand human speech, but speech
synthesis is what is needed to help the machine respond in kind. Machine learning has advanced
significantly in the synthesis of natural-sounding voices in recent years.
With just a few hours of training data, we create speech synthesis models that generate natural-sounding
speech using custom voices. These models help our clients automate customer calls and provide prompt and
personalized messages to users, for example, in the event of a service outage.
However, speech synthesis has a wider range of applications and is actively used
to create audio versions of written articles and even audio books. Although the quality isn’t quite as
good as when it’s read by someone with a deeper understanding of the material and a wider cultural
context, it’s still a useful tool.
Speech synthesis
Speech recognition allows a machine to understand human speech, but speech synthesis is what is needed
to help the machine respond in kind. Machine learning has advanced significantly in the synthesis of
natural-sounding voices in recent years.
With just a few hours of training data, we create speech synthesis models that generate natural-sounding
speech using custom voices. These models help our clients automate customer calls and provide prompt and
personalized messages to users, for example, in the event of a service outage.
However, speech synthesis has a wider range of applications and is actively used
to create audio versions of written articles and even audio books. Although the quality isn’t quite as
good as when it’s read by someone with a deeper understanding of the material and a wider cultural
context, it’s still a useful tool.
Speaker identification
Knowing who is speaking is often as crucial as understanding their message. This can be very useful for
meeting memos, automatic subtitling, customer identification, and even for law enforcement needs.
Speaker recognition is one area where machines very often outperform humans, not only in recognition
accuracy but also in the number of people these systems can accurately identify. As with humans, this is, of
course, strongly affected by the quality of the sound. For example, speaker recognition in a phone call is
inherently less accurate than in a recording of a meeting.
However, Speaker identification has a wider range of applications and is actively used
to create audio versions of written articles and even audio books. Although the quality isn’t quite as
good as when it’s read by someone with a deeper understanding of the material and a wider cultural
context, it’s still a useful tool.
Emotion detection
Emotions can be determined from audio in a similar fashion to sentiment analysis in text. This is even more
important here since speech recognition itself is imperfect, and people focus less on the tone of words when
voice can be used.
This is particularly important when speaking with customers over the phone since it helps to understand how
strongly they feel about the reason for the call, or when contacting emergency services because the emotion
in the caller’s voice can indicate the urgency of the call.
Our projects
Language learning platform using NLP
A conversational interface with its own voice, Annika takes calls from
clients, listens to what they have to say, and directs them to the best course of action.
This is done using multilingual speech recognition to translate speech to words, transformer based
NLP models to understand the content of a customer’s sentence and non-autoregressive Transformer
based text to speech models that provide Annika with her signature voice.
Building a job search and career development platform requires quite a bit of
data collection - user profiles, job descriptions, cover letters, etc. We designed a system that
takes user provided documents - CV-s, cover letters, job and education descriptions, etc. - as input
and, using transformer based language models, extracts the relevant information that fits the data
model of the platform.
Our Sentiment Analysis Tool uses NLP and machine learning to detect
emotions and identify potential tax fraud. Deployed at the EstonianTax and Customs Board, it enhances
compliance and enables smarter, data-driven decisions. The system continuously
learns from expert auditors to improve accuracy and efficiency over time.
Our Summarization Tool leverages NLP to process and analyze data captured by
drones,
helping power line utilities efficiently inspect their grids. Using the specialized uBird inspection
platform,
the system extracts key insights, streamlines reporting, and supports faster, data-driven decisions.
The Innverse team brings extensive experience in machine learning development,
AI implementation, and custom AI solutions, enabling us to hit the ground running on your project.
With a team of highly qualified specialists, we don’t waste time figuring out how to work
efficiently
— we already know the best practices, tools, and workflows to deliver results quickly and
effectively.
WWe carefully allocate the right experts to your project based on their specific skill
sets, whether it’s for one day or six months,
ensuring that your AI initiative progresses smoothly and efficiently. By leveraging our deep
expertise in AI project execution, predictive analytics, and enterprise AI solutions, we can
significantly shorten your learning curve and accelerate the delivery of high-impact, business-ready
AI solutions.
Unlocking the potential of AI
Since our inception, we’ve successfully built a reputation of trust, reliability and
of
delivering exceptional services. We are progressively diversifying into new markets with our
battle-hardened methodologies. Every day, we work to empower our customers to get the maximum
out of
technology.
We challenge, we innovate, and we continue to deepen our knowledge and expertise to
realize the best value for our customers. We do this through a culture that cultivates a
relationship-based approach to helping people and businesses be successful.
Waseem Ahmad
Frequently ask question
Discovering the right process to be enhanced with AI may be an unusual task for business
people.
People should come to us when they have a business problem where they intuitively feel that the
solution could be hidden in data and that it can not be solved by writing a couple of simple
rules. If this is the case, AI might be the solution.
To actually define an AI use case, business leaders will need the help of an AI team, who judge
if and how to proceed with the problem enhancement; the problem owner who knows the most about
the issue; and technical specialists who understand how the problem described by the problem
owner can be interacted with in the technical world.
Data collection is most often on the client side as it is connected to
the peculiar business problem to be solved we help as much as we can, especially if it is a data
source we have worked with before.
Labeling can be on the client side if very specific knowledge is required for labeling or it can
be outsourced to a labeling company or us. Hybrid solutions are also available, and in all
cases, we provide proper labeling training and guidelines tailored to the computer vision task.
If you imagine the process made up of iterations of the cycle: data
collection, labeling, model development + training, testing & evaluation and deployment into the
final solution, usually the first 2 steps take 20-50% of the time (the smaller the project /
standard problem, the higher the percentage) while the split between the latter 3 is really
dependent of the novelty of the problem being solved, the required performance level and the
complexity of deployment. The AI project range is from 3 months to multi-year collaborations.
During the project evaluation, we provide a feasibility assessment, and
for problems in which we have experience, we can provide a more precise prediction and discuss
the forecasted minimum level of performance.
How can we help you?
Are you ready to push boundaries and explore new
frontiers of innovation?
Let's Talk
Why contact us?
Validate your situation with our business advisors and IT executives
Understand business results, not just technical implications
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