Customer Service Automation · IT Operations Automation
CoreWeave needed to route customer issues to the right engineers faster, reduce the manual context gathering and tool handoffs in its Slack-centric support process, and do it without letting sensitive customer data leave its own security perimeter.
Reported impact
CoreWeave transformed its customer support in 90 days, cut mean time to resolution from 4-8 days to 2-5 days, sustained 4.9 - 5.0 CSAT scores, improved routing accuracy, and gave engineers more time to solve problems instead of chasing context across disconnected tools.
CoreWeave rebuilt its support workflow around Cohere North, deploying the agentic AI platform privately inside its own data centers and embedding it directly into Slack through APIs rather than forcing teams into a separate chat surface. When a new issue arrives, North's triage bot gathers customer context such as region, cluster, and other account details from CoreWeave's backend record-keeping systems, then presents the prefilled ticket to a customer support engineer for review. After the engineer confirms or edits the details, internal automation opens a Jira issue and a swarming channel, where a second North resolution agent retrieves documentation and historical post-ticket reviews to recommend the next steps. North's multi-model architecture let CoreWeave fit different models to different tasks while keeping privacy, control, and support-team speed aligned.
A customer issue arrives in Slack, North's triage bot pulls region, cluster, and other customer context from backend systems, a support engineer reviews and confirms the ticket, Jira opens the swarming workflow, and a North resolution agent uses documentation plus post-ticket reviews to suggest the next steps for engineering.
4.9 - 5.0 customer satisfaction (CSAT) scores
A separate internal automation creates a Jira issue
Because North would be privately deployed inside CoreWeave’s own data centers, sensitive customer data never leaves their security perimeter
North can be integrated via API into existing business software, workflows, and automations. For CoreWeave, that meant they could embed North directly into their preferred support system: Slack.
North collects and pre-populates key customer context, such as region, cluster, and other customer-specific information from CoreWeave's backend record-keeping systems.
On average, CoreWeave’s resolution time decreased from 4-8 days to 2-5 days
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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