The Conversation Intelligence Cloud for scaling 100% QA and real-time agent performance.
Observe.AI is a category-leading Conversation Intelligence platform designed for the modern contact center. Its technical architecture leverages proprietary Large Language Models (LLMs) and Generative AI to analyze 100% of customer interactions across voice and text channels. Unlike traditional sampling methods, Observe.AI provides a comprehensive data layer that automates Quality Assurance (QA) workflows, redacts PII/PCI data for compliance, and generates post-call summaries to reduce After-Call Work (ACW) by up to 80%. By 2026, the platform has solidified its market position as a primary orchestrator of Agent Performance Management, moving beyond simple transcription into predictive behavioral modeling. Its Real-Time AI engine provides live-agent assistance, surfacing relevant knowledge base articles and sentiment-driven talk tracks during active conversations. The platform integrates deeply with CCaaS leaders like Genesys, Talkdesk, and Zoom, creating a closed-loop system where conversational data informs executive-level business intelligence. Its 2026 roadmap emphasizes 'autonomous coaching'—where the AI identifies skill gaps and pushes personalized micro-learning modules to agents without human supervisor intervention.
Uses fine-tuned LLMs to generate structured, human-like summaries of every call, identifying problem, action, and resolution.
Empower customer service representatives with real-time generative AI insights and automated knowledge retrieval.
The Enterprise-Grade Platform for Scaling Autonomous AI Agents in Customer Service.
Real-time emotional intelligence and behavioral guidance for high-performance contact centers.
The first Large Language Model purpose-built for human-to-human conversational intelligence.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Low-latency stream processing that monitors live calls to trigger on-screen prompts based on customer intent.
Machine learning models that score every interaction against customized rubrics without human input.
Domain-specific acoustic and language models optimized for contact center terminology and diverse accents.
Pattern recognition engine that detects specific behaviors, such as 'Dead Air,' 'Empathy,' or 'Supervisor Escalation' automatically.
Deep learning NLP models identify and scrub sensitive digits (SSN, CC) from both audio and text.
Unified data processing for voice, chat, email, and social messaging interactions.
New agents take months to reach peak productivity and compliance standards.
Registry Updated:2/7/2026
Manual QA misses legal disclosure errors, leading to regulatory fines.
Management doesn't know why top performers sell more than others.