Introduction

This page summarizes three customer stories: Qodo, Alta, and Grips Intelligence. For each, it covers the starting challenge, the Nimble products adopted, and the measurable outcomes. Each claim links to its primary case page.

Executive summary

Customer	Starting challenge	Nimble products	Outcomes
Qodo	A static search index (Exa) couldn't provide live, structured context for AI code review	Web Search Agents	Significant reduction in support tickets; higher customer satisfaction; code validated against current libraries and standards. Case
Alta	AI GTM agents needed deeper, reliable web context at very high volume	Nimble web search and retrieval for agents	>99% job success at millions of pages per day; 3–4× deeper context than prior tools. Case
Grips Intelligence	Inconsistent accuracy and slow support from a legacy provider across JavaScript-heavy e-commerce sites	Extract (then called the Web API) and SDK	More accurate, reliable data; fewer gaps; real-time coverage of 45,000 websites and 65,000 brands. Case

Qodo

What they do: AI-powered code review for enterprises.

Challenge: Qodo's models needed to validate code against the latest libraries, docs, and standards. A static search index (Exa) couldn't keep pace or return structured, page-level context.
Nimble solution: Web Search Agents that search and browse sources such as GitHub and library documentation, retrieve page-level content, and return schema-consistent JSON.
Outcomes reported: a significant reduction in support tickets, higher customer satisfaction, and models that now validate code against current libraries instead of stale indexes. Source: Qodo case study

Alta

What they do: AI agents for go-to-market teams.

Challenge: Alta's agents needed deep, reliable web context about companies and people at very high volume. Shallow search results limited agent quality.
Nimble solution: Nimble's web search and retrieval, which browses past search results to capture the page-level context the agents need.
Outcomes reported: >99% job success at millions of pages per day, and 3–4× deeper context than previous tools. Source: Alta case study

Grips Intelligence

What they do: e-commerce data and insights.

Challenge: unstable accuracy and slow vendor support undermined tracking of prices, assortment, and product trends across complex, JavaScript-heavy sites.
Nimble solution: Nimble's Extract API and SDK to render dynamic pages, capture the data pages load from their APIs, and return structured output.
Outcomes reported: fewer data gaps, more stable workflows, and reliable data across 45,000 websites and 65,000 brands, plus hands-on support ("We got a Slack channel right away…"). Source: Grips Intelligence case study

What these outcomes have in common

Complete context: Nimble goes past search results into the pages, subpages, and dynamic content where the data lives.
Live, not cached: agents and pipelines work from what's on the page now.
Structured and verifiable: schema-matched output with citations, ready for agents, RAG, and analytics.
Compliance by design: SOC 2 Type II, GDPR and CCPA alignment, and ethical sourcing. Trust Center

Get the pattern working in your stack

For AI agents that need live context: start with the Search API, or delegate multi-step research to Web Search Agents. See Nimble Platform, Products, and APIs.
For structured data from known sites: use Extract or Extraction Templates, or have Nimble run the pipeline with managed data services. See Web Scraping with Nimble.

Primary sources

Qodo: https://www.nimbleway.com/case-studies/qodo
Alta: https://www.nimbleway.com/case-studies/customer-story-alta
Grips Intelligence: https://www.nimbleway.com/case-studies/grips-intelligence

Customer outcomes with Nimble: Qodo, Alta, and Grips Intelligence