DataRoot Labs

DataRoot Labs was hired by AVITAR, an AI-powered legal document automation platform. The goal was to develop a proof of concept (PoC) for a generative AI model that could automatically populate legal documents from templates. The platform included functions such as a library of templates, customization capabilities, automatic population of templates with relevant information using NLP and machine learning algorithms, and a search function. Following the release of the PoC, DataRoot Labs was tasked with improving model performance and adding new features. The team from DataRoot Labs, comprising 2-5 employees, successfully delivered on the project objectives.

In another project, DataRoot Labs was engaged by a social audio marketplace startup. The main task was to build AI-powered audio content recommendation algorithms based on user data and behavior. The team from DataRoot Labs also handled some data engineering tasks and all AI tasks related to the core product of the company. The deliverables included the successful creation of a sophisticated audio content recommendation engine that provided valid recommendations on the content tabs within the application. The team also improved existing recommendation algorithms and added new features.

DataRoot Labs worked with a startup company aiming to bootstrap trust and legitimacy to the web to prevent abuse by cybercriminals. The company needed DataRoot Labs to build a system that would bring a market-driven allowlist capability to an Intelligence Sharing Platform, using computer vision recognition of crawled pages of domains for block/takedown. The deliverables included a Software Requirements Specification document, a Computer Vision engine, and the development and testing of a CI/CD pipeline. The team from DataRoot Labs successfully developed and tested the system before deploying it.