Case Study: Orbit Financial Technology turns unstructured data into trading ideas with Naviga

Orbit Financial Technology turns unstructured data into trading ideas

Orbit Financial Technology, a London-based data-analysis company, needed a better way to gather and process large volumes of unstructured news and filings so it could focus on its core strength: building machine-learning models for trading signals. Instead of spending resources on crawling, latency management, and data normalization, the company wanted a more flexible, transparent, and scalable data source for its QuantLab product suite. Naviga provided the content-as-a-service foundation Orbit needed.

With Naviga’s CaaS and ACME taxonomy, Orbit could access historical and real-time news data across thousands of sources, filter content by region, language, and country, and feed it directly into its natural language processing and prediction models. Naviga helped Orbit expand coverage from 400 to a potential 4,000 websites, accelerate implementation in just a couple of weeks, and lower costs by including historical data that other vendors would charge extra for. As a result, Orbit was able to focus on analytics and deliver faster, more targeted trading signals with a transparent, configurable model.

Orbit Financial Technology

Da Wei

Founder