This startup offers an AI-powered text analytics platform that enables users to query, summarize, and extract insights from large volumes of text data, significantly reducing research and development time by 75%. By clustering documents into topics and utilizing a custom GPT model for enhanced Q&A, the platform democratizes access to efficient data processing and analysis for research and enterprise applications.
Funding
$450K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
BCVGFounders
Product
Problem
Research and development processes often involve sifting through vast amounts of unstructured text data, which is time-consuming and resource-intensive. Extracting relevant insights and identifying key themes from these large datasets presents a significant challenge for researchers and enterprises.
Solution
Delv AI offers an AI-powered text analytics platform designed to streamline research workflows by enabling users to efficiently query, summarize, and extract insights from extensive text datasets. The platform employs a clustering engine to organize documents into topics and subtopics, providing a structured overview of the data. Users can leverage a custom GPT model to perform question-answering across multiple documents, facilitating consensus-building and knowledge discovery. By automating key aspects of data processing and analysis, Delv AI aims to reduce the time and effort required for research and development tasks.
Target Audience
The primary target audience includes researchers and enterprises seeking to optimize their research and development processes through efficient text analytics and AI-powered insights extraction.
Features
- AI-powered clustering engine for organizing databases into topics and subtopics
- Connectivity to cloud drives and open-source data sources
- AI-generated visualizations, including pie charts, treemaps, and heatmaps
- Custom GPT model (OpenAI Assistant API) for question-answering across multiple documents
- Reinforcement Learning from Human Feedback (RLHF) to improve answer accuracy with continued usage
- Custom context addition for enhanced answer relevance
- Result saving and exporting capabilities
- Compliant data privacy measures
- On-prem hosting (coming soon)
- Customizable topics and labels for the clustering engine (coming soon)
- Self-training AI model (Personalized LLM Training) (coming soon)