Swisscom builds a multi-agent Network Assistant on Amazon Bedrock to reduce engineer data-retrieval time by 10%
Swisscom network engineers spent significant time manually gathering and analyzing data from multiple decoupled sources, with certain tasks consuming more than 10% of engineer availability, introducing risk of human error and preventing focus on strategic work.
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 · Engineer submits natural language query
A network engineer submits a query in natural language to the Network Assistant.
The Network Assistant is estimated to deliver a 10% reduction in routine data-retrieval time per engineer, saving nearly 200 hours annually per engineer, at operational costs less than 1% of total value generated, enabling engineers to focus on strategic tasks.
What failed first
The initial RAG implementation struggled with large input files containing thousands of rows of numerical data, and the retrieval process did not return the precise number of vector embeddings required for accurate KPI formula calculations.
Results
Time saved10% reduction
Volumenearly 200 hours per engineer saved annually
Cost replacedless than 1% of the total value generated