Internet, media and advertising are the key informational sources for a modern man. What they have in common is that they serve a ready-made product, just like we get a dish in a restaurant. And similarly, we do not think about amounts of information, like products in the fridge, that need a highly qualified cook to present it all in a useful way.
Information and analytics stepped into a whole new territory when the technologies of artificial intelligence and machine learning emerged. Huge business databases began to build up everywhere, as well as new sciences and trades, such as “Big data”. Modern digital systems are capable of detecting patterns in databases faster than humans. But who makes, manages and maintains those systems? How is big data designed?
InData Labs is one of such big data companies, with over five years of gathered experience. Their portfolio includes projects related to big data analytics, computer vision development, artificial intelligence (AI) integration. They also provide consulting and business intelligence services to customers from all over the world.
Key facts about InData Labs:
| Established | 2014 |
| Service lines | Big data development/consulting, AI software development, data analysis, BI implementation, predictive analytics, machine learning (ML), intelligent automation, computer vision |
| Employees | 50-100 |
| Avg.hourly rate | $50-99 |
| Locations | Belarus, Cyprus, USA, Singapore |
They collaborate with several universities exploring data science projects and also have their own research and development center. This allows InData Labs to cater to customers in mid-level and top-level market. The team consists of experienced business analysts, AI developers and machine learning engineers.
InData Labs pays great attention to communication with its customers. This is expressed mainly via the ability to talk to any team member directly, and constant coordination throughout each development stage. Thus, projects meet both customer’s requirements and engineers’ recommendations.
Business data and insights could mean an upper hand over competitors. Let’s see what services does InData Labs provide. Those are machine learning and artificial intelligence, big data, business intelligence.
Depending on customer requirements, project development may include: data channels differentiation, key parameters detection, environment for big data processing, integration of unknown data channels, or other stages.
Big data storage is dependant on multiple factors. For existing data processing systems, InData Labs experts can conduct a technical analysis - in order to identify vulnerable components and/or the potential. They can also integrate new interfaces into an existing system, ensuring proper interaction between all components.
So far, data engineers have successfully implemented dozens of projects related to data systems, including real-time data analysis. Own research center allows the team to constantly experiment with mathematical algorithms, market simulations, and then apply the findings as proprietary algorithms.
The use of artificial intelligence grants an opportunity to make crucial decisions based on large amounts of data. InData Labs also actively explore Machine Learning, utilizing samples databases that can be extended for specific customer data. Several patents in speech recognition and computer vision serve as a solid proof.
Nowadays, AI is in use all around already, starting from security (face block on iPhones), transport (autopiloting Teslas), to food production (defective item removal). As for InData Labs, for one of customers they developed a system that detected brand mentions in YouTube videos and forums.
Due to use of personal data by most of AI systems, InData Labs pays great attention to the issue of data protection. Also, projects might be affected by customers’ national laws or corporate guidelines.
Proprietary tools go along with best existing 3-rd party services, e.g. Python, Spacy, Pytorch, Gensim, Tensorflow, Keras, Theano, Dmlc xgboost, Scikit-learn, Prophet.
For consulting InData Labs has three specific groups:
1. Data science group (basic concepts of AI and Big Data)2. Data engineering group (assistance in Machine Learning)3. Business units (across-the-board advice on data processing systems)
BI solutions rely on many years of experience in data processing. The effectiveness always depends on data source quality and further processing. Therefore, InData Labs helps customers to properly configure data collection in the first place.
Very often, this includes automation. For instance, the automated delivery permit after order confirmation will remove several decision-making steps. That, in part, will enable a company to process more orders without additional employees.
InData Labs suggests customers ways/approaches to increase data efficiency. Firstly, it could be universal data systems. It then translates into clear hardware requirements and risk minimization.
Secondly, data unification algorithms aimed to simplify maintenance. Customers may also order tools to visualize the accumulated data, reporting and forecasting tools, etc. Afterwards, in close cooperation between company designers and customer, user-friendly interfaces are created.
InData Labs was hired to enhance the functionality of influencer marketing platform and make real-time social media analytics possible. The platform was built and automation of working process added. As a result, the overall productivity has improved significantly and infrastructure costs reduced.
InData Labs implemented a neural network for Flo - a smart tracker that accurately predicts women’s menstrual cycles, ovulation, and fertile days. The main goal was to improve cycle predictions. In result, it helped better the predictions by 55% and reduce error margins from 5.6 to 2.6 days. Flo became the most downloaded app worldwide in its category within months after.
For 81 weeks lasted the project, with the task to complement the existing analytical platform with ways to attract new Facebook users. Through a series of tests, competitions and applying relevant tools (JavaScript, MongoDB, PostgreSQL), they built a sophisticated social media scoring software that led to thousands of newly registered users.
For a global game developer with 150 million audience, undisclosed for obvious reasons, InData Labs’ challenge was to automate customer feedback from YouTube and forums. Additionally, they also implemented a custom NLP model trained to understand the slang of a particular game.
A 21-week long project aimed at improving the existing project management system and creating/integrating a microservice designed to evaluate projects duration on its own, and with a high degree of accuracy. More details in the portfolio.
A UK data company assisting other businesses in banking, finance, healthcare, etc. with an AI-based platform required to tackle the issue of unstructured raw data. InData Labs’ team had to build a data lake, a centralized repository in other words, as a BI solution. The following tools and technologies were involved: Apache NiFi, Cloudera CDH, Apache Oozie, Apache Spark, HDFS, Apache Kudu, Apache Impala.
Let the words of Flo CTO, Andrew Kovzel, one of the biggest and most representative projects by InData Labs, be the closing statement to our review.
“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.”
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