sales_ops · finance · workflow

TP ICAP builds ClientIQ with Amazon Bedrock to cut CRM research time by 75%

TP ICAP had accumulated tens of thousands of vendor meeting notes in their CRM that were being underutilized, with business users spending hours manually searching through records knowing the information existed but unable to efficiently locate it.

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 · User submits natural language query
Users submit natural language queries about their Salesforce meeting data.
Tools used
Amazon BedrockAmazon Bedrock Knowledge BasesAmazon Bedrock EvaluationsAmazon Titan v1Amazon OpenSearch ServerlessAmazon AthenaAWS GlueSalesforce · partnerReactOktaRAGSOQL
Outcome

Following the initial launch with 20 users, ClientIQ delivered a 75% reduction in time spent on research tasks, and stakeholders reported an improvement in insight quality with more comprehensive and contextual information being surfaced.

Results
Time saved75%
Volume20
Source

https://aws.amazon.com/blogs/machine-learning/how-tp-icap-transformed-crm-data-into-real-time-insights-with-amazon-bedrock?tag=soumet-20

How we source this →

Grounding & classification
Source type: platform led case
39 fields verified against source quotes, 8 dropped as unverifiable.
conversational aidata extractionenterprise searchragsummarizationknowledge basemetric backednamed customerproduction runtime claimedsource backedtools describedvendor confirmedworkflow describedfinancial servicesemployee productivitytime savedplatform led caseback office opssales opsextract classify routerag answering