Aderant Speeds Up Cloud Operations 10x With Amazon Quick

Aderant deployed Amazon Quick and unified search across six disparate vendor systems. The AI-powered setup made search 10 times faster and sped up document handling by 75%. It is a practical example of taming chaos in cloud operations.

AI-processed from AWS Machine Learning Blog; edited by Hamidun News
Aderant Speeds Up Cloud Operations 10x With Amazon Quick
Source: AWS Machine Learning Blog. Collage: Hamidun News.
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Article Fact Sheet & Key Figures
ParameterDetails
Primary sourceAWS Machine Learning Blog ↗
Editor-in-Chief
Key metric #1Unified search across all systems at once
Key metric #2Automatic indexing of documents and metadata
Key metric #3AI suggests where to look

Aderant used Amazon Quick, an AWS AI tool, to unify search and automate document work. The result: search runs 10 times faster, and document workflow is 75% faster.

Aderant's problem

It is a familiar situation at a growing tech company: data is scattered across six systems from different vendors. When an engineer or documentation specialist needs information, they have to search through separate interfaces, switch between tabs, and spend an hour on something that should take five minutes.

How Amazon Quick helped

Amazon Quick made it possible to build a single entry point for search across the whole stack. AI-powered indexing automatically structures data from all six sources, and results come back instantly.

  • Unified search across all systems at once
  • Automatic indexing of documents and metadata
  • AI suggests where to look
  • Natural-language support: questions instead of keywords

Practical results

Search got 90 percent faster: instead of several minutes, answers arrive in a few seconds. Documentation that used to be updated by hand is now reconciled and structured by the system itself. This takes 75% less time.

What this means

For mid-sized and large companies with multiple cloud systems, this is a practical path: instead of integrating everything in-house, they can use a ready-made AI layer on top of what they already have. Search becomes a core operation rather than a bottleneck.

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Key Questions Answered

What are the key details on Aderant's problem?

It is a familiar situation at a growing tech company: data is scattered across six systems from different vendors. When an engineer or documentation specialist needs information, they have to search through separate interfaces, switch between tabs, and spend an hour on something that should take five minutes.

How Amazon Quick helped?

Amazon Quick made it possible to build a single entry point for search across the whole stack. AI-powered indexing automatically structures data from all six sources, and results come back instantly. Unified search across all systems at once Automatic indexing of documents and metadata AI suggests where to look Natural-language support: questions instead of keywords

What are the key details on Practical results?

Search got 90 percent faster: instead of several minutes, answers arrive in a few seconds. Documentation that used to be updated by hand is now reconciled and structured by the system itself. This takes 75% less time.

ZK
Zhemal Khamidun — CPO at Alpina Digital, product manager of AlpinaGPT. Building AI products since 2019. Hamidun News is a pet project that grew into a production aggregator with 6,000+ readers.
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