anec.app provides OnClarity, an agentic customer experience (CX) platform that listens to, reasons about, and acts on customer conversations while verifying outcomes and continuously learning from them. The platform scores every interaction, updates its knowledge base with approved fixes, and closes the loop to prevent recurring issues, reducing costly operational gaps.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional CX AI systems operate as an open loop: signals go in, answers come out, and nothing returns—so the same gaps reappear quarter after quarter. Without verification, scoring, or feedback, incorrect answers and knowledge gaps go undetected, creating costly failures and operational inefficiencies.
Solution
OnClarity is an agentic CX loop that listens, reasons, acts, verifies, and learns from every conversation. It uses an AI Support Agent to handle tickets, then an AI QA function scores each interaction against a consistent rubric locked to the knowledge base. A "Brain Guard" continuously updates approved knowledge articles and rules, ensuring future answers are grounded in verified sources. This closed loop turns every interaction into a learning signal, progressively improving resolution quality and reducing manual QA and knowledge maintenance.
Target Audience
Enterprise customer support operations, especially national service operators and organizations handling high inbound call or ticket volumes that need to reduce manual QA, close knowledge gaps, and improve AI answer reliability.
Features
- Automated ticket resolution via an AI Support Agent that references approved knowledge-base articles and policy rules
- Agent QA scoring of every conversation on the same rubric, with reason codes for any failures
- Brain Guard knowledge maintenance that writes new rules and articles from verified conversation outcomes
- Closed-loop verification that ensures answers are tied to approved sources, preventing unverifiable or wrong responses
- Real-time dashboard showing tickets, resolutions, handovers, scores, and knowledge fixes per interaction
- Independent analysis capabilities to calculate operational costs like manual insight compilation and per-agent QA evaluation