Kapiche

What Kapiche is

Kapiche analyzes customer conversations from surveys, support, reviews, social media, calls, chat, email, and CRM data to produce customer intelligence. Teams can upload CSV or XLSX files or bring data in through integrations. Its AI enrichment classifies conversations by contact reason, sentiment, escalation risk, and satisfaction signals. Kapiche also says it can flag at-risk customers and emerging issues from conversation patterns to predict churn. Its AI-powered quality assurance scores conversations against custom frameworks, including empathy, resolution, and compliance. Integrations include Zendesk, Salesforce, Genesys, Five9, Qualtrics, Snowflake, Slack, Tableau, and Microsoft Teams. An MCP server lets compatible assistants query feedback when site access and permissions allow. Kapiche is offered on the web and through an API. Pricing is paid, from $1,060/mo, with no free plan or trial; the Bronze plan is listed at $2 a month. Kapiche says it encrypts data in transit and at rest, holds a SOC 2 Type II report available under NDA on request, and has compliance capabilities for HIPAA, PCI, and GDPR.

Who it suits

Kapiche describes its intended users as customer experience and support leaders, executives, and product teams. It may suit teams that need to analyze feedback from several channels and track quality or customer risk.

Limits

Kapiche has no free plan or free trial. The Bronze tier lists 50,000 rows and 10 fields per project, two creator seats, five explorer seats, and unlimited viewer seats; higher tiers specify their own row, field, source, and seat limits.

Getting started

1. Open the Kapiche website
2. Select a paid plan or contact sales for a listed Talk to sales tier
3. Upload project data as CSV or XLSX files
4. Connect supported integrations such as Zendesk, Salesforce, or Qualtrics
5. Use Kapiche through its web interface or API
6. Connect a compatible assistant through the MCP server with required access and permissions

Verdict

Kapiche combines multi-channel feedback analysis with predictive signals and conversation quality scoring. Its entry pricing and lack of a trial are important considerations for teams evaluating it.