Case Study
Challenge
From AI Search to AI Understanding
Qodo is an AI-powered code review platform helping enterprises standardize software quality in the era of generative coding.
As developers increasingly rely on AI coding assistants, the volume of auto-generated code has exploded; sometimes thousands of lines in minutes.
To ensure that code aligns with best practices, Qodo needs fresh, reliable, and context-rich data from across the web, including GitHub repositories, open-source libraries, and even domain-specific websites relevant to their customers’ products.
As Qodo’s product scaled, these limitations began to surface in two critical areas:
- Freshness
Embeddings captured static data that quickly went stale. - Depth
Exa could locate a page, but not extract the structured insights within it.
Solution
Going Deeper with Web Search Agents
Qodo turned to Nimble’s Web Search Agents to replace Exa and power their next generation of AI-driven quality checks.
Unlike search engines, which depend on static indexes, Nimble’s agents actively browse, render, and extract data from the live web, capturing the full, dynamic state of each page at the moment it’s needed.
This shift allowed Qodo to:
- Retrieve real-time GitHub data on library versions, dependencies, and usage patterns.
- Access dynamic websites that previously couldn’t be indexed.
- Scale reliably across a diverse mix of data sources—from open-source projects to private ecosystems—without compromising performance.
Impact
Higher Quality, Happier Users
Since integrating Nimble, Qodo’s technical team reports a significant reduction in support tickets and higher customer satisfaction - a direct reflection of the improved accuracy and reliability of their code review outputs.
With Nimble’s real-time web access, Qodo’s AI models now validate code against the latest open-source libraries and standards, ensuring that enterprise customers always work with current and correct information.
