DataRoot Labs

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Overview

$10,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

10 - 49

Employees

2016

Year Founded

ABOUT DATAROOT LABS

R&D as a service for Data Science & AI Startups

DataRoot Labs is a recognized company that specializes in creating and implementing Artificial Intelligence, Machine Learning, and Data Engineering solutions across various industries to assist clients in developing and launching AI-driven products and services. Since our inception in 2016, we have focused exclusively on AI development and consulting, cultivating extensive in-house expertise in areas such as Generative AI, Conversational AI, Natural Language Processing, Computer Vision, Machine Learning, Reinforcement Learning, Deep Learning, Edge ML, and more. Based in the US, we serve a global clientele, benefiting from the strong mathematical and scientific skills of Ukrainian engineers. To give back to the community, we operate DataRoot University—an online platform offering free courses in machine learning and data engineering. Since 2018, more than 6,000 students have joined, enhancing our connection to a dynamic AI community and aiding in the recruitment and development of top talent for both our team and the wider industry.

Languages Spoken

EnglishSpanishUkrainian

HIGHLIGHTS

$10,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

10 - 49

Employees

2016

Year Founded

Services

Focus

Industries

Clients

Services Provided+6 Services

10% AI Strategy & Roadmap Consulting

9% LLM Integration & Prompt Engineering

8% Custom AI Chatbot Development

12% Machine Learning Model Development

3% Robotic Process Automation (RPA)

5% AI-Powered Document Processing

2% Workflow Automation (Zapier / Make / n8n)

7% Computer Vision Solutions

About the Team

OUR STORY

Our Narrative We are DataRoot Labs (DRL) — a group of specialists dedicated to enhancing the growth of the Data Science and AI sectors in Ukraine. Since 2016, we've been developing research and development projects for financially backed startups from Europe, Israel, and the US. We take pleasure in tackling intricate AI tasks using cutting-edge technologies and solutions. The more challenging the project, the more enjoyable it is for us. Our team comprises not just enthusiasts and professionals, but also individuals with a strong determination to accomplish tasks effectively.

TEAM PHOTOS

Portfolio

Optimizing Fleet Efficiency with AI-driven Routing

Unknown

Request: The client, who runs a rapidly growing business with large vehicles that need specialized equipment spread over a wide area, experienced significant difficulties in route planning. Drivers often had to change tools throughout their workday, complicating and making manual route planning ineffective. The client aimed to reduce operational costs and boost efficiency by adopting a system that could manage vehicle routes dynamically in real-time, taking into account various business constraints and unforeseen events. Solution: To tackle these issues, DRL created an AI-powered dynamic route management system. This solution employed advanced Vehicle Routing Problem algorithms and integrated mapping APIs to optimize vehicle routes according to the client’s business goals. The system utilized real-time data, including live traffic updates and road conditions, enabling immediate route modifications in reaction to unexpected incidents such as job cancellations or equipment breakdowns. By factoring in elements like fuel consumption, driver workload distribution, equipment availability, and delivery schedules, the system significantly lowered transportation costs and enhanced overall operational efficiency. Read the complete case study here: https://datarootlabs.com/blog/optimizing-fleet-management.

AI Agent for Lead Management

Unknown

**Request**: For many B2C companies, reaching out to leads is resource-intensive and time-consuming, while converting those leads requires substantial effort to attract customers. Our team was assigned to create a conversational AI agent capable of handling voice calls and chat interactions. This agent exhibits various conversational styles, adapts its dialogue strategies based on client responses, and gathers information to facilitate decision-making and streamline workflows. The solution was designed to significantly lower the costs of call center support while increasing lead outreach. **Solution**: The DRL team utilized ElevenLabs for natural and approachable text-to-speech synthesis, minimizing the chances of being perceived as spam. Deepgram was implemented on our own servers for speech recognition, providing low latency and high-quality interactions. A decision-making model, such as OpenAI's 4o-mini, dynamically adjusts the flow of conversations in real time to enhance interaction smoothness. Furthermore, LLM-based entity recognition captures essential lead information, while a retrieval system enables the agent to access pertinent data for more accurate and context-specific responses. The agent has greatly reduced the amount of time sales managers spend on lead outreach by automating initial communications and routine tasks like note-taking, following up, and sending meeting links. For more information on how DRL automated lead interactions and decreased operational costs, visit: https://datarootlabs.com/blog/ai-agent-for-lead-management.

AI-Powered Cognitive Wearable for Pets

Unknown

**Request**: The client is a startup creating a wearable device for pets that features speakers and sensors facilitating communication between pets and their owners. DataRoot Labs was tasked with developing an intelligent, real-time communication system integrated into the wearable device, which utilizes cloud-based machine learning for dialogue, sound detection, and activity recognition, personalized by caregiver voice responses and a robust pipeline for event-driven alerts. **Solution**: The DataRoot Labs team developed a comprehensive real-time system for voice interactions, emotion recognition, and activity understanding through sensors. For general conversations, they implemented a streaming response generation system, alongside a custom-designed virtual character that represents user-chosen personas. The team refined a voice cloning system by conducting extensive experiments to enhance audio quality. They improved keyword detection with a model that could learn new trigger words from just a few audio samples, bypassing the need for full retraining. Emotion detection utilized both audio classification and text analysis to capture a broad spectrum of user expressions. All models were optimized for GPU inference and were deployed through a scalable infrastructure that supports concurrent execution and dynamic batching. For the complete case study, click here: https://datarootlabs.com/blog/wearable-for-pets

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