it_support · saas · workflow

Adobe enhances developer productivity with Amazon Bedrock Knowledge Bases, achieving 20% improvement in retrieval accuracy

Adobe's internal developers relied on vast wiki pages, software guidelines, and troubleshooting guides with no centralized system, making it difficult to efficiently find information for troubleshooting and software upgrades. An initial Unified Support prototype confirmed the approach but revealed scalability gaps, complex resource onboarding, poor content synchronization, and infrastructure inefficiency.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Data ingested from S3
Data is pulled from Amazon S3 buckets, including resolutions to past issues and wiki pages.
Tools used
Amazon Bedrock Knowledge BasesVector Engine for Amazon OpenSearch ServerlessAmazon Titan V2Ragaslangchain-aws
Outcome

The Amazon Bedrock Knowledge Bases solution achieved a 20% increase in retrieval accuracy compared to Adobe's existing solution, enabled seamless document ingestion and synchronization, scaled to support thousands of Adobe developers, and contributed to reduced support costs.

What failed first

Adobe's initial Unified Support prototype confirmed the potential of the approach but exposed scalability limitations, resource onboarding complexity, content synchronization gaps, and infrastructure inefficiency that prevented it from operating at Adobe's scale, requiring a new retrieval precision focus.

Results
Volume20%
Cost replacedreduced support costs
Source

https://aws.amazon.com/blogs/machine-learning/adobe-enhances-developer-productivity-using-amazon-bedrock-knowledge-bases?tag=soumet-20

How we source this →

Grounding & classification
Source type: technical build writeup
25 fields verified against source quotes, 1 dropped as unverifiable.
enterprise searchknowledge searchragknowledge basefailure mode describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedsoftwareaccuracy improvementcost reductionemployee productivitytechnical build writeupit supportdata sync enrichmentrag answering