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Machine Learning Development Services

Generate valuable insights and go beyond your digital potential with our machine learning development services tailored to your business requirements
Machine learning has penetrated all areas of business and is changing the way progressive companies work. InData Labs is a trusted AI and machine learning development company that offers a wide range of advanced software services to help businesses efficiently overcome complex challenges and maximize their profits. Our ML engineers have years of experience handling everything from building tools to optimizing channels to deliver a sustainable ML-powered ecosystem for any business industry or size.

Trusted by Innovative Companies

Power up Your Business with the Right ML Use Case

Turn your ideas into high-quality software solutions with our expert machine learning development services. Unlock your business potential with:
  • data analysis

    Big Data Analytics

    We can provide operational analytics and visualization for business decisions to accelerate time to insights and let your employees shuffle off the burden of manual monitoring and analyzing numerical data.
  • generative ai

    GenAI & NLP

    Integrate ChatGPT and NLP solutions to derive momentum data insights, boost customer engagement, and maximize your performance.
  • icon visualization

    Predictive Analytics

    InData Labs helps build custom predictive analytics models that let you forecast trends, customer behavior, and ROI and accelerate your organization past your competitors.
  • icon vision

    Computer Vision

    Leverage the power of computer vision to amplify process efficiency and automate business by extracting real-time data from videos and images.
Thinking of AI adoption?
Let's talk your vision through

Our Approach to ML Development Services

Our unique InData Labs approach was designed through years of experience to solve pitfalls hindering business performance and outcomes and make the most out of automation and innovation.
  • icon consulting
    Free consultation
    First: a no-obligation consultation to understand your business needs and goals. Next: a tech call to dig to the core of your project and choose the best starting point for it.
  • data
    Data Preparation
    We clean and validate your data, to ensure its usefulness, make sure nothing is missing, and that private data is masked.
  • engine quality
    Model Building
    Based on your requirements, we can create an ML model dedicated to your needs and adapted to the data you use. We can also fine-tune your open-source model at request.
  • icon-testing-qa
    Testing
    ML models created at InData Labs are comprehensively tested to ensure their high performance based on KPIs set.

Implement Machine Learning Model and Receive

Boundless opportunities opened up for you with the right-suited custom machine learning app development.
  • Recommender systems

    Better Decision-Making

    Exploit vast amounts of information to enhance your business processes, optimize the workforce & deliver strategic growth.
  • Improved Visibility

    Boost in Production Efficiency

    Identify patterns, make accurate predictions about market trends and customer behavior, and build the best-fit products accordingly.
  • Intelligent Transport

    Reduced Human Error

    Harness machine learning to eliminate the human factor, prevent analysis errors, and maximize performance with lightning speed.
  • icon five stars

    Enhanced Customer Experience

    By developing AI-powered chatbots and virtual assistants using machine learning, you can improve customer satisfaction and increase conversions.
  • security

    Better Security

    Integrating machine learning helps predict malicious activities (malware, phishing, app & authentication attacks), detect and prevent security threats.
  • Custom AI Solutions

    Sales Support

    Anticipating and responding to users' demands, AI chatbots have the potential to provide quality real-time human-like support increasing sales.
  • increase

    Higher Employee Productivity

    Automated jobs can be performed by machine learning algorithms, freeing up human resources to focus on higher-value and more complex work.
  • bi implementation

    Comprehensive Research

    A machine learning app can decide on the best delivery date and pricing, as well as analyze customers’ buying habits and act upon them.

Machine Learning Model Development Life Cycle

At InData Labs, we have developed a streamlined system for turning your ML ideas into reality. From planning to maintenance, we work to adhere to businesses' needs and help you scale up your presence in the market.
  • 1. Discovery
    You explain your business specifics and goals and share your pain points to gain insights into ML capabilities and an approach designed by our machine learning developers.
  • 2. Preparation of the ML model
    This stage includes all activities aimed at preparing an effective ML model, such as data preparation, data mining, data engineering, model training, and verification.
  • 3. Model evaluation
    At this stage, we prove that chosen ML use cases can (or cannot) deliver tangible value to your organization — and to choose those worth moving forward with.
  • 4. Model deployment
    Our team builds automated pipelines, scales, and deploys your machine learning app into production. We also adjust algorithms to meet your desired benchmarks.
  • 5. Monitoring & maintenance
    Delivering the solution isn’t the end of the journey. We’ll continue to work with you and make updates and changes to the system’s environment as required.

Best Tech Stack to Develop Machine Learning Algorithms

We harness the latest developments in machine learning and relevant programming languages to build solutions for our clients. We apply the right stack to develop a machine-learning model that is future-proof and solid.
  • technology python
  • openAI
  • Pytorch technology
  • technology tensorflow
  • technology spark
  • apache technology
  • technology scikit learn
  • postgre sql technology
  • technology elastic
  • azure machine learning
  • aws sagemaker
Not sure what technologies you need?
Contact us, and we will help you to make the right choice!

Work with Seasoned Machine Learning Developers

Companies from different countries and industries choose InData Labs as an experienced and trusted ML development company that offers profound expertise combined with real-world vision.
  • Business-First Approach
    Your business needs are our top priority. That’s why we put a particular focus on the planning and consulting stage. All the processes from research prototyping to testing and deployment are performed to help you reach your goals, not just for show.
  • Vetted Team of Professionals
    We are backed up by a strong team of ML experts who think outside the box and come up with innovative solutions for machine learning software development. You can stay assured that we will develop a high-quality machine learning application.
  • Trustworthy Partner
    Our proven track record underlines that any business domain can benefit from our customized AI and machine learning app development services. Your idea and data will stay safe, while our team will leverage the accrued expertise to your benefit.
  • Affordable & On-Time Delivery
    We understand the value of time and money for any business in a competitive business environment. That’s why InData Labs strives to deliver outstanding services meeting all the deadlines and maximizing the pay-off you receive with a final ML product.
  • Client Participation
    Regardless of the development stage of your ML solution, you will never get left behind unaware of the current product status. We update our clients on the completed and ongoing tasks and are ready to implement changes if required.
  • Sophisticated Technology
    We keep up-to-date with cutting-edge tools and technologies to offer highly advanced solutions. Leverage our expertise and capabilities to better upgrade and reinforce your business models by developing high-end machine learning algorithms.

Let Our Clients Do the Talking

  • Reviewed on Clutch
    Pavel Nurminskiy
    Pavel Nurminskiy
    Head of Machine Learning at Creative Research, Wargaming

    If you want to have a stable and efficient product, I recommend working with InData Labs.

    They created an anti-fraud solution for our company, implemented and improved algorithms, and collaborated to deliver a working product. InData Labs’ work helped us save a significant percentage of our marketing budget. Clients can expect a partner who excels at delivering products.

  • Reviewed on Clutch
    Ivan Akulovich
    Ivan Akulovich
    Project Manager of Business Development Department, AsstrA

    The competitiveness of InData Labs in the field of data science impressed us. More importantly, we learned many things from them.

    InData Labs built a new freight rates prediction software for our company. The increased quality of the data results we received dramatically improved our metrics. InData Labs did an excellent job and became our trusted data science partner.

  • Vishal Gurbuxani
    Vishal Gurbuxani
    Co-Founder & CTO, Captiv8

    Without InData Labs we wouldn’t have gotten all the exclusive data from social media that we offer to our customers today. With no doubt, I highly recommend InData Labs for any big data related projects.

  • Reviewed on Clutch
    Eudis Anjos
    Eudis Anjos
    Senior Engineering Manager of GSMA

    InData Labs completed the deliverables on time and met our expectations. They recommended improvements and shared ideas for new features. We appreciated the team’s friendly approach, engagement with the project and the friendliness.

    They were like part of my team, I had the confidence to reach any of the team members at any time. It was as if we were working in the same physical environment.

  • Reviewed on Clutch
    Brent McCarthy
    Brent McCarthy
    CEO & Co-Founder, Myka LLC

    Not only is the team fully capable of delivering what we want, but they also deliver in a timely manner.

    Thanks to our team at InData Labs, we were able to quickly correct all issues/bugs from our previous developers, while implementing a custom algorithm for our most pertinent feature of our app, artificial intelligence. They turned our app around from unusable to outstanding and marketable in a matter of months.

  • Reviewed on Clutch
    Andrew Kovzel
    Andrew Kovzel
    CTO, Flo: Smart Period Tracker

    As a growing company, we found InData Labs’ expertise in data science invaluable. In almost two years of our cooperation, they’ve helped us define our data analytics strategy, build a scalable data pipeline, and improve menstrual cycle predictions with a sophisticated neural network.

  • Reviewed on Clutch
    David Cairns
    David Cairns
    CEO & Co-Founder, Skorebee

    We have used InData Labs help us create not only the scoring models, but also build frontend and backend components which have all been completed with high quality, within expected timelines, and with clear visibility into ongoing status. The InData team think in terms of being a long-term partner…not just a provider, and I would recommend them to anyone who values intelligent, diligent & proactive development partners.

  • Reviewed on Clutch
    CEO and Co-Founder of an Spinout from the University of Copenhagen

    Their competence in data science, machine learning is second to none. The algorithms and methods were extremely well-explained and documented. We were likewise impressed by the friendly and proactive engagement we got from every member of the team. We’re a very small organization with a limited budget, but they always treated us like our problems and our business was of utmost importance. In short, we got the same level of service that a company 1000x our size would have gotten.

  • Reviewed on Clutch
    Head of Business Development, Corporate Start-Up

    Their drive was strong, and the whole team pushed their limits to meet deadlines and make everything work. Their strengths showed throughout our collaboration.

    Give them a try, even with small projects to test them out. They won’t disappoint you, and they’re very open about what they can and can’t do. I would recommend them to anyone.

Looking for custom ML algorithms?
Talk to us about how we can help you cut down time and money costs, automate operations, and enhance efficiency.
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FAQ

  • Machine learning (ML) is a direction of AI focused on the creation of systems that are trained and developed based on the data they receive. ML opens up new possibilities for computers to solve tasks previously performed by humans and trains a computer system to make accurate predictions when entering data.

  • The ML model development involves data acquisition from multiple trusted sources, data processing to make it suitable for building the model, choosing algorithms to build the model, building the model, computing performance metrics, and choosing the best-performing model.

  • InData Labs offers machine learning consulting and development services. Our team of ML engineers has proven expertise in Big Data analytics and visualization, integrating natural language processing and ChatGPT, predictive analytics, and computer vision. We provide our clients with quality deep learning solutions development, custom web application development, and enterprise machine learning as a service (MLaaS) solutions to enhance their business efficiency and gain insights unseen before.

  • Artificial intelligence and ML have become game-changing technologies in the digital era enabling machines to learn from data, identify patterns, and make decisions based on the insights generated. AI and ML development consists of consulting, designing, and implementing AI and ML applications to enhance businesses’ operations and stay ahead of their competitors in the market.

  • The best-suited languages for developing a machine learning solution are said to be Python, R, Julia, Java, JavaScript, and C++. Yet, each of them is worth considering, offers unique strengths, and caters to different project requirements.

    Python simplifies the implementation of complex machine learning algorithms, R is the best for data analysis and visualization, Julia allows for faster execution of code, Java offers robust scalability, while C++ provides unparalleled performance for computationally intensive tasks.

  • The technology is subdivided into three major types – supervised, unsupervised, and reinforcement learning:

    With supervised learning, the source data is already sorted out in the required way, and the algorithm only has to determine the object with the desired feature or calculate the result. Such models are used in spam filters, text recognition, fraud detection, and health anomaly identification.

    Unsupervised learning implies that the machine itself must find the right solution among the chaotic unstructured data and sort out objects by unknown features. This model is used for data that cannot be marked because of its enormous volume.

    Reinforcement learning is a more complex model where the algorithm doesn’t only analyze the data but acts independently in the real environment. Its task is to minimize errors and learn from them, which allows it to keep working without obstacles and failures.

  • Implementing an ML model allows businesses to analyze huge amounts of unstructured data and act upon the insights, provide personalized services, embrace automation, and thereby save time and money expenses.
    It also helps to stay ahead of competitors and take a glimpse of the future by anticipating trends and customer behavior.

  • The ML technology is one of the directions of artificial intelligence. Unlike programs with manually coded instructions for specific tasks, ML allows the system to learn to recognize templates and make predictions on its own. That’s why, machine learning always implies the use of AI, while AI is not always machine learning.

  • The average cost to develop an Artificial Intelligence or machine learning app will range between $35,000 to $150,000 and more. However, it is just a rough estimate. The final cost of ML development depends on the project requirements, product functionalities, project size, and others.

  • The technology is a rapidly growing point of focus for companies across all industries. It has the potential to personalize marketing campaigns and anticipate sales, predict and treat diseases in Healthcare, improve logistics efficiency and customer satisfaction, analyze market trends and risk factors in Fintech, and improve the performance of each.

  • First, ML-based automation reduces the human factor and helps employees focus on more complex tasks, which improves work efficiency. Anticipating future patterns and analyzing tons of data allows for better decision-making and dodging unwanted mistakes. What’s more, its deep analysis enables businesses to provide personalized experience, which significantly enhances customer service and boosts conversion rate.

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