Data Science & AI
implement artificial intelligence
build machine learning models
adopt predictive analytics
We provide artificial intelligence consulting to help organizations implement this technology today.
We use Machine Learning tools and algorithms 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.
Our team is experienced in:
- Machine learning
- Deep learning & neural networks
- Natural language processing
- Predictive modeling
- Reinforcement learning
- Anomaly detection
Providing machine learning development & artificial intelligence consulting to startups and large enterprises 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.
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.
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.
- Neural networks improve predictions in healthcare
From the case study, you will learn why one of the top-rated mobile apps for female health “Flo” turned to InData Labs for artificial intelligence consulting and how neural networks can improve predictions in healthcare.
