Source reconciliation and enrichment
Connect feedback sources so they inform each other, with deduplication, noise cleaning, normalization, and reconciliation that improve as more integrations are added.
Zefi AI is a voice-of-customer and feedback analytics platform for CX, product, QA and marketing teams. Unify feedback, structure insights and take action.
Zefi AI is a voice-of-customer and feedback analytics platform that helps teams unify customer feedback from multiple sources, structure it, and act on it. The product is positioned for CX, product, QA, and marketing teams that need a clearer view of what customers are saying and a system for turning those signals into workflows.
Its core workflow combines source reconciliation, in-product surveys, analytics, AI-assisted analysis, and automation. The site emphasizes that feedback sources enrich each other automatically, every insight stays traceable to its source, and teams can use alerts or agents to close the loop without manual handoffs.
Connect feedback sources so they inform each other, with deduplication, noise cleaning, normalization, and reconciliation that improve as more integrations are added.
Collect NPS, CSAT, and qualitative responses with in-product surveys that use targeting, behavioral triggers, timing, and branching logic.
Structure unstructured feedback into taxonomy, topics, sentiment, mention extraction, metadata segmentation, and cleaned datasets ready for analysis.
Use dashboards, analytics, an AI assistant, and opportunity mapping to spot recurring issues, trends, and measurable signals across customer feedback.
Send alerts, digests, and workflow automations to tools such as Slack, Jira, and Linear, or use agents to trigger actions automatically.
Review support quality with AI QA scorecards designed to surface coaching gaps and performance issues.
Bring customer feedback from different channels into one place, clean and reconcile the data, and keep each insight linked to its source so the team can trust the output.
Trigger surveys at the right moment inside the product, using behavior or context to collect NPS, CSAT, or open-ended feedback from relevant users.
Use dashboards and the AI assistant to identify recurring problems, trends, and similar feedback patterns, then translate them into roadmap or operational decisions.
Send alerts, digests, and workflow actions to Slack, Jira, Linear, or similar tools so teams can respond without manually moving feedback around.
Review support interactions with AI QA scorecards to spot quality gaps and support coaching opportunities.
Zefi appears to ingest feedback from multiple connected sources and reconcile it into a single system of record, with every insight linked back to its source. The pricing page also says the system works across connected sources and that new integrations make the system more granular and accurate.
The source pages describe in-product surveys with smart targeting, timing based on behavior or context, and branching logic for collecting NPS, CSAT, and qualitative feedback. They are presented as part of the core product rather than a separate survey tool.
Zefi’s pages describe analytics dashboards, an AI assistant for quick questions, opportunity mapping, alerts, workflow automation, and agents that can launch workflows or send notifications to the right owner.
The pricing page shows a modular subscription with a core plan and add-on modules such as Survey, QA, Brand, Product, and Customer Intelligence. It also lists an Enterprise option with custom terms.
The public pages show integrations with tools such as Slack, Jira, and Linear for alerts and workflow automation, but they do not provide a complete integration catalog in the text provided.