Hexo provides an AI-powered platform that automatically extracts entities from unstructured data—including PDFs, audio, video, images, and web content—and outputs structured formats such as JSON, CSV, or SQL. The system’s self‑improving models and scalable cloud architecture enable continuous, low‑latency data pipelines for enterprise analytics teams, reducing manual processing costs.
Funding
$270K 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.
AIFounders
Product
Problem
Enterprises often need to extract actionable information from large volumes of unstructured data such as PDFs, audio, video, images, and web content. Manual processing of these sources is time‑consuming, error‑prone, and costly, which hampers operational efficiency and scalability.
Solution
Hexo delivers an AI‑powered platform that automatically converts unstructured data into structured formats (e.g., JSON, CSV, SQL) across a wide range of file types. The system leverages machine‑learning models to recognize and extract relevant entities without human intervention, enabling 24/7 data pipelines. Hexo also offers an open‑source Self‑Improving AI (SIA) framework that continuously refines its extraction models, reducing the need for ongoing manual tuning. The platform is built on a scalable cloud infrastructure, allowing enterprises to expand processing capacity without proportional cost increases.
Target Audience
Hexo’s primary customers are data engineering and analytics teams within large enterprises, especially in sectors such as intellectual property, government, banking, and finance that handle extensive unstructured content.
Features
- AI‑driven extraction engine that parses PDFs, audio, video, HTML, images, JSON, XML, CSV, and SQL files.
- End‑to‑end automation that creates structured datasets ready for analytics or downstream applications.
- Continuous self‑improvement via the open‑source SIA framework, which updates models based on new data.
- Scalable cloud architecture that supports high‑volume workloads while maintaining low latency.
- API and SDK integrations for seamless embedding into existing data pipelines and enterprise systems.
- Cost‑reduction through minimized manual data entry and reduced operational overhead.