Data Science & AI

InData Labs can help you

build data-driven apps

implement artificial intelligence

adopt advanced analytics

InData Labs provides data science services to help tech startups and enterprises leverage machine learning technologies and build breakthrough AI products.

We use Natural Language Processing (NLP), Machine Learning, and Predictive Modeling to help companies develop AI-driven products and solutions that act human like. Our team has profound knowledge and experience in designing, implementing and integrating Artificial Intelligence solutions within the customer’s business environment.

Providing data science services to startups and enterprise clients we noticed that although the company structures may be totally different, both startups and enterprise clients face the same challenges planning new data initiatives. Our clients either don’t have their own data science teams, or their team is too small to cope with all the tasks in the environment of a fast-growing company. Our data science services help companies save time on hiring top notch specialists. We provide a team of world-class data scientists that bring know-how to your project from day one.   

Our team is experienced in: 

  • Machine learning
  • Text analytics
  • Predictive modeling
  • Pattern recognition
  • Data Mining
  • Anomaly detection
  • Graph analytics

A typical data science project workflow consists of the following steps:

  • Data Assessment

    Reviewing current capabilities to make recommendations for tools, teams, and processes.

  • Proof of Concept

    Experimenting with data sets to prove the viability of mathematical models for customer’s business case.

  • Implementation

    Inserting mathematical models into production while considering costs of implementation and maintenance during deployment.

  • Improvement

    Modernization of previously built models to continuously raise the quality of insights.

Starting with a clearly defined business case, data scientists review available data and current capabilities of a client to make recommendations for tools and data management processes that are necessary for future success. They then collect all the useful data and generate a mathematical model. Before moving forward data scientists prove the viability of the model for customer’s business case.

Solution fit to the customer’s business case is of high priority for us. There is no single technology, tool or algorithm that would be applicable to different use cases. For us, every single problem has a very particular answer. Our data scientists work within customer’s team to optimize workflow and ensure the best outcomes.

We successfully cooperate with different teams within your company:

  • Data Science teams: In cases when a company already has a data science team we become a valuable asset bringing profound expertise in certain areas of data science, such as deep learning, text analytics, data mining, and pattern recognition.
  • Engineering teams: machine learning may not be a key expertise of a company. In this case, we are working with an existing engineering team providing the API of a machine learning system that fully corresponds to our clients’ needs and requirements. This way we allow them to focus on primary tasks rather than try to learn an entirely new discipline.
  • Business units: this type of cooperation often starts with developing a proof of concept for a business unit. Typically the stakeholders are non-technical people who have very “high level” goals. We work closely with them breaking down this goal into logical steps, defining and prioritizing use cases, and providing the best solution for each of them in order to achieve complex results. 
Customer Success
  • Advanced analytics adoption in a digital health startup

    From the case study, you will learn how big data analytics revolutionizes healthcare domain and why one of the top-rated mobile apps for female health “Flo” turned to InData Labs for advanced analytics adoption.

Have a project in mind? We'll make it happen!