DataRoot Labs
About DataRoot Labs
DataRoot Labs is an award-winning company that builds and implements Artificial Intelligence, Machine Learning and Data Engineering systems across industry verticals to help our clients build and launch AI-powered products and services.
Since 2016, we have specialized exclusively in AI development and consulting, building deep in-house expertise in Generative AI, Conversational AI, Natural Language Processing, Computer Vision, Machine Learning, Reinforcement Learning, Deep Learning, Edge ML, and other related areas. We are a US company with a global client base, leveraging the math and science excellence of Ukrainian engineers.
As a way to give back to the community, we run DataRoot University — a free, proprietary online school focused on machine learning and data engineering. Since 2018, over 6,000 students have enrolled, giving us access to a vibrant AI community and helping us attract and develop top talent for our team and the broader market.
Our Culture and Values
DataRoot Lab is a team of AI experts that has been delivering R&D solutions for startups, SMBs, and enterprises across the US, UK, Europe, and beyond since 2016. We thrive on complex AI challenges and enjoy building state-of-the-art solutions using new technologies. The tougher the problem, the more exciting the project.
Our team is more than just a group of AI enthusiasts — it's a collective of skilled professionals with a strong get-things-done mindset. We're experienced in working with startups in fast-paced environments, delivering results on budget, and without unnecessary bureaucracy.
For enterprise clients, we collaborate directly with R&D teams to co-develop AI solutions that automate processes and create a competitive edge.
Regardless of the client, we prioritize efficiency, practical solutions, speed, clear communication, and ease of doing business.
DataRoot Labs is an award-winning company that builds and implements Artificial Intelligence, Machine Learning and Data Engineering systems across industry verticals to help our clients build and launch AI-powered products and services.
Since 2016, we have specialized exclusively in AI development and consulting, building deep in-house expertise in Generative AI, Conversational AI, Natural Language Processing, Computer Vision, Machine Learning, Reinforcement Learning, Deep Learning, Edge ML, and other related areas. We are a US company with a global client base, leveraging the math and science excellence of Ukrainian engineers.
As a way to give back to the community, we run DataRoot University — a free, proprietary online school focused on machine learning and data engineering. Since 2018, over 6,000 students have enrolled, giving us access to a vibrant AI community and helping us attract and develop top talent for our team and the broader market.
Our Culture and Values
DataRoot Lab is a team of AI experts that has been delivering R&D solutions for startups, SMBs, and enterprises across the US, UK, Europe, and beyond since 2016. We thrive on complex AI challenges and enjoy building state-of-the-art solutions using new technologies. The tougher the problem, the more exciting the project.
Our team is more than just a group of AI enthusiasts — it's a collective of skilled professionals with a strong get-things-done mindset. We're experienced in working with startups in fast-paced environments, delivering results on budget, and without unnecessary bureaucracy.
For enterprise clients, we collaborate directly with R&D teams to co-develop AI solutions that automate processes and create a competitive edge.
Regardless of the client, we prioritize efficiency, practical solutions, speed, clear communication, and ease of doing business.
Key Insights
Services & Focus
Industry Focus
Client Focus
Portfolio
Optimizing Fleet Efficiency with AI-Driven Dynamic Route Management
The client has a fast-growing business with oversized vehicles that use specialized equipment stored in locations spread over a large area. Drivers use this equipment to work at client sites and often need to change their tools during the day.
The client faced challenges in manually planning vehicle routes due to multiple business constraints, such as varying fuel consumption rates, driver workload balancing, equipment availability, and unpredictable events like sudden job cancellations or road conditions. They needed a solution to minimize operational costs and improve effectiveness by dynamically managing routes during the working day.
To address these challenges, we developed a system based on the enhanced Vehicle Routing Problem algorithm and map APIs. This solution reduces transportation costs by optimizing vehicle routes to align with the client’s business objectives, ensuring efficient resource use and real-time adaptability.
Case study: https://datarootlabs.com/blog/optimizing-fleet-management
AI Agent for Lead Management
For most b2c businesses the leads' outreach consumes a lot of resources and time, while the conversion rate requires intensive work to attract clients;
Business optimization infers the goal of involving AI in those areas of the sales workflow that are reasonable, especially for initial communication to reduce the cost of leads processing;
Our team developed a conversational AI agent capable of performing voice calls and chat interactions. The agent follows various conversational behaviors, adapts dialogue strategies based on client responses, and collects information to simplify the decision process and further workflow;
The developed solution helped to significantly decrease the price of call center support while increasing leads coverage.
Case study: https://datarootlabs.com/blog/ai-agent-for-lead-management
AI Robotics and Simulation for Enhanced Quality Control
An inventive client startup is revolutionizing the use of AI robotics in manufacturing. The company focuses on high-mix production, which involves making different types of products with various specifications.
They intended to develop a simulation to identify product’s deformations using sensors to scan details and compare them with perfect parts. Therefore, we employed this solution to deal with some high-mix manufacturing problems and to increase accuracy and productivity in processes.
The team used the NVIDIA Omniverse Isaac Sim platform to make an advanced simulation, with the integrated client’s robot prototype created in Onshape. A critical component was point cloud comparison using CloudCompare software for accurate and fast identification of discrepancies in manufactured parts.
Case study: https://datarootlabs.com/blog/ai-robotics-for-enhanced-quality-control
AI-Powered Recommendation Engine for a Leading Health App
The client is a popular weight loss app that focuses on changing behavior to adopt a healthy lifestyle and appearance. The app makes it entertaining to build new habits as part of a supportive community. Among other features, it enables users to listen to live sessions from wellness coaches, other experts, and leading voices.
To increase user engagement and loyalty, the client imagined building a recommendation engine as a core function of the app. Its key task would be an effective matching system between user goals and preferences AND relevant live streams and health-related trending topics.
Our team has developed an AI-powered recommendation engine that works with both audio and text formats. By leveraging a siamese-architecture-inspired network, the system considers multiple parameters to produce relevant and engaging content recommendations.
Case study: https://datarootlabs.com/blog/recommendation-engine-health-app
AI-powered Market Research Agent for B2B Sales
The client is a B2B software company offering IT consulting and development services. Their customers praise their work for exceptional technology expertise and continue to choose them as a preferred partner for IT-related tasks. Most of their new clients traditionally come from referrals and a personal network while outbound sales had limited results.
To build a diversified and predictable outbound revenue stream, the client decided to develop a platform that would automate prospect searching and outreach. The tool would not only replace most of the existing capabilities of the human market researcher on the team but also significantly increase prospect sources and their volume.
The built system would need to automatically find relevant prospects based on a defined customer profile, look up fresh information on each prospect, and create personalized outreach campaigns based on the findings. For example, a cold email campaign targeting companies with a certain position on their website that would also include insights from recent company news published on their blog.
DataRoot Labs successfully developed an AI-driven Market Research Agent for the client. This solution generates a daily list of relevant prospects based on pre-defined filters, provides the latest insights on each company, and crafts personalized outreach campaigns. As a result, the client enjoys a substantial increase in response rate and sales calls, with dozens made each month.
Virtual Wine Consultant for a Wine Company
The client is a global wine discovery and marketplace platform. They created a membership-based wine community to unite wine enthusiasts, share knowledge, and assist in creating unique wine collections.
The client decided to develop a Conversational Agent who would assist wine collectors by answering questions about different wines in their storage (cellar) and their characteristics. Additionally, the Agent can answer general questions about the wine industry and all wine varieties. The final solution would be feasible in Metaverse, with a virtual consultant available through the company's VR add-on.
A system has been developed leveraging API-based LLMs. OpenAI GPT-3.5 and a set of customized models for question classification, embedding creation, and named entity extraction power the solution. Milvus served as the vector database for knowledge storage. This tech stack combination built up the search engine and made the agent interactive.
Knowledge & Memories Agent for Bookstore
The client operates a bookstore with various titles spanning genres, authors, and eras. This store is not just a commercial entity but a hub for literary enthusiasts, providing curated collections, rare editions, and a space for readers to delve deep into the world of literature.
The client envisioned a Conversational Agent that would serve as a knowledgeable companion for customers. This agent would possess in-depth knowledge of the content of books on sale and a vast understanding of classic literature. Beyond just answering queries, the agent should recommend books based on user questions. Furthermore, it would have a 'memory' of past interactions, allowing it to offer personalized recommendations based on previous conversations with the user.
A system was built using entirely API-based LLMs. The main LLMs for generation and embeddings were GPT-3.5 and ada-002. We used Pinecone for knowledge & memory storage. This combination allowed the Conversational Agent to provide insightful book recommendations and maintain interaction continuity.
Knowledge AI for Oracle NPC in MMORPG
The client is developing a massively multiplayer online role-playing game (MMORPG) set in a vast, immersive fantasy world. This world is rich in lore, characters, quests, and items, offering players a deep and engaging gameplay experience. The game boasts a dynamic environment where players can interact, form alliances, and embark on epic adventures.
The client envisioned an innovative feature for their MMORPG: an Oracle Non-Player Character (NPC) that players could approach and consult. This Oracle would serve as an in-game knowledge base, answering players' questions about the game's lore, mechanics, or personal progress. Notably, the Oracle's knowledge would be gated, revealing information only in line with a player's in-game achievements and progress.
A sophisticated knowledge system was implemented to bring the Oracle NPC to life. At its core, the method utilized the LLaMa 2 as the primary LLM. Milvus, a robust vector database, managed and retrieved vast amounts of in-game data. The embedding of this data for efficient querying was achieved using the SetFit algorithm, ensuring that players received accurate and contextually relevant answers from the Oracle.
Digital Transformation of a Large Telematic Service
Our client is a telematics service used for truck fleet management. Technically, their solution is a mix of sophisticated software and hardware for collecting and analyzing critical information about vehicle and driver parameters in real-time, allowing customers to manage their fleet with a high degree of efficiency and at the lower cost.
The client strove to augment driver's safety and security and enhance the driving experience by digitally transforming its obsolete software into a modern platform powered by AI, able to track the large number of fleet vehicles in real-time.
Our team designed and implemented different parts of the final product, including APIs, web-interfaces and mobile apps, with the main challenge to create the system which receives the data from hundreds of thousands of monitoring devices in real-time, working 24/7.
CV-Powered Personal Coach Platform for Amateur Athletes
Our client develops a platform that provides access to the best coaches in ballet, dancing, martial arts among other sport types.
The platform enables aspiring sportsmen to learn different physical activities by using their own devices anytime anywhere. Through any phone or computer camera, the platform compares athlete's movements to the ones of a professional coach while providing live analytics and recommendations on how to improve the performance of each move. We used advanced Computer Vision technologies to build an end-to-end MVP that enables professional-to-student physical activity learning from any mobile device.
Case Study: https://drl.direct/ai-personal-coach
CV-Powered In-store Customer Behavior
The store chain client wanted to track the number of people walking in and out of her stores as well as their behavior inside the store.
Our team has built a solution that through a video camera tracks where people walk inside the store, identifying their gender and age category. The above had to be calculated in real-time using the setup located in the store – Dual-Core Celeron + GTX 660 2Gb.
Case Study: https://drl.direct/cv-store
ML-Powered Data Warehouse for SERP Analytics
Modern approaches for monitoring the site position inside global and local search engines require huge amounts of different textual queries. A leading digital marketing agency wanted a scalable and automated service, dedicated to performing search engine optimization analysis. The agency used such an engine for day-to-day and long term analytics and monitoring of the performance of SEO optimized sites. NLP and other ML methods were the foundations of the solution implemented by our team.
Case Study: https://drl.direct/ml-dwh-serp
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