InData Labs

InData Labs has developed an AI solution that uses computer vision technologies like object detection and pose estimation for automated aggression detection of cattle operators directed against cows. This solution has been developed for a US-based client from the cattle industry to enable a safe environment for cattle keeping them healthy and providing sustainable livestock production for farmers.

The InData Labs team was challenged with ChatGPT prompt engineering for their own website virtual assistant development. They aimed at building their own Conversational AI chatbot for business process automation and customer human-like interaction. The result of the work is a fine-tuned ChatGPT-4 virtual website assistant that uses deep learning algorithms and massive datasets to help InData Labs website visitors get assistance with both quick and complex queries about the services and expertise of the company, as well as with arranging the calls with sales representatives based on location.

InData Labs was challenged to develop a robust AI system both the front- and backend (and IOS application) aspects of the app and the AI algorithm integration. The work has resulted in a sophisticated AI mobile app - the voice-powered & interactive recipe recording app for cooking enthusiasts. The AI-enabled kitchen assistant makes cooking fun records and reads recipes with the users voice, stores all the data so the user will never forget ingredients again.

InData Labs was challenged to create a multi-channel marketing automation tool that helps manage and enhance ad performance based on automated audits of users’ online stores and current advertising initiatives and objectives. As a result, the Client can now provide an intelligent commerce tool to store owners for campaign automation and competitive marketing. The tool covers all steps of creating and optimizing a winning ad campaign based on real-time and historical data analysis. Users can get an advertising audit with observations and recommendations to increase performance as well as access personalized forecasting with machine learning predictions based on historical data.

The Client is was looking for a more efficient way to analyze the chemical composition of mixtures and products as well as their test results. InData Labs was chosen by the Client as a tech partner with seasoned Big data analytics solutions and Machine Learning consulting services. As a result of our collaboration, we have transformed the Client’s data stack and delivered a tailored advanced data analytics solution that drastically improved decision-making, real-time analytics, and insight extraction.

The client deals with huge amounts of data coming from various sources regularly. They wanted to scrape job offers, mentorship and network opportunities for talented African American entrepreneurs from various websites and publish it on their own platform. So, entrepreneurs can easily discover businesses owned by African Americans and go support them or locate their own. InData Labs was challenged to develop a strong data scraping solution for the client’s marketplace. Our team drew upon multiple sources to meet the client’s data scraping needs. As a result, the client has got a robust data scraping solution that scrapes data from multiple sites and business listings and gathers information about businesses’ founded by African Americans that are useful for the subscribers of the client’s platform.

The Client needed to make accurate freight rate predictions for the forwarding agents to rely on the system’s analysis. Our team has advanced the Client’s existing freight predictive rate solution significantly. The Client’s recognized our deep expertise in predictive analytics software development, commitment to excellence, and timely delivery.

We were challenged to develop a data solution from scratch, considering different data input formats, such as Excel files and PDFs, and their correct processing, enrichment, and integration to enable all the features planned in the web app which was being developed in parallel. Our team built a reliable cloud infrastructure based on AWS that makes it possible to extract and process users investment data to simplify and add value to investment management.