Contact center leaders recognize the transformative potential of generative AI to enhance operational efficiency, improve customer experience (CX), and drive revenue. But, there have been many barriers to deploying Gen AI solutions — complex implementations, resistance to adoption by agents, and lack of customization to business needs. In addition, generic AI models are famously prone to hallucination, putting the business at risk of costly downstream repercussions including legal challenges, ethics, data privacy, and security concerns. The technology landscape is increasingly hard to navigate with overhyped promises, failed proof of concepts, and deferred projects.
Creating a Definitive Path to Value
At Observe.AI, we are relentlessly focused on our customers’ success and time to value. As we infuse Gen AI innovations into contact center workflows, our emphasis is on easy configurability, fast implementation, accuracy, and security to accelerate value from Gen AI investments – in some cases in as little as three weeks.
While earlier approaches to conversation intelligence have relied heavily on keywords and phrases to extract precise yet narrow insights, deriving insights based on complex reasoning and broader subjective questions has remained a key challenge. With this new release, Observe.AI enables customers to tackle this last frontier using natural language prompts to extract more nuanced, subjective, and ambiguous insights.
For example, contact centers can easily answer questions like “Did the agent respond appropriately to customer objections?” or “Did the agent ask probing questions to understand the customer’s issue?”. These insights then enrich Auto QA, coaching, and real-time agent guidance at the speed and performance required by enterprise contact centers. Now contact center leaders no longer have to struggle with incomplete or inaccurate insights and slow, complex implementations.
A leading healthcare firm achieved a 50% reduction in after-call-work with 80% adoption across its 1500 agents. Customers work with our product teams as early adopters and design partners to ensure Gen AI solutions are enterprise-hardened and prove ROI even before we release them.
A Moment for Every Business Insight
Moments is the foundational architecture for insights in the Observe.AI platform. Moments can be based on keywords and phrases, to detect, for example, script and disclosure adherence that improve compliance. There’s a large library of pre-built Moments that are common to most contact centers, for example, agent greeting and ending, agent overtalk, and customer complaints. Our sophisticated and easy to use Moment Builder helps contact center leaders seek insights that are bespoke to the business.
Announcing Gen AI Moments
Observe.AI is expanding its powerful Moments architecture, enabling Moments to be created using natural language prompts. This new feature further increases our industry-leading Auto QA coverage by accurately automating nuanced and subjective QA questions such as “Did the agent understand the customer’s issue?”. Moments are easy to set up, and the Observe.AI platform builds in human-centric feedback for continuous learning.
These insights enrich real-time agent guidance, Auto QA, and personalized coaching workflows at the speed and performance required by enterprises.
Automation of Call Notes, Customized for Your Business
A significant challenge for contact center agents is the manual effort required for call summarization and after-call notes, leading to longer average handle time (AHT). Manually created summaries often lack the structure and consistency needed to derive business insights at scale, while summaries generated by generic large language models lack the accuracy and completeness needed for full automation in contact centers. Both challenges degrade downstream workstreams, resulting in increased operational costs and unreliable insights.
Observe.AI Summarization AI enables tangible outcomes immediately, with predefined categories including "reason for the call", "key events", and "next steps". Summarization AI also provides flexibility to automatically generate customized summaries that eliminate after-call-work in both Real-Time AI and Post-Interaction AI.
To further tailor summaries to the business, Observe.AI now provides Summarization Builder, a powerful feature that gives users control to freely create, customize, and tailor interaction summaries in one intuitive dashboard allowing for:
- Specific alphanumeric entities (e.g., competitors, offers or products mentioned during the interaction)
- Choice-based inputs (e.g., customer sentiment was positive, negative, or neutral)
- Free-text responses (e.g., answers in paragraph or bullet points)
After-call notes structured to business workflows can then be pushed directly to CRM, Ticketing, HRIS, and other business systems using Observe.AI Integrations to help the business extract insights that improve revenue, retention, and operational efficiency.
“Observe.AI’s large language model empowers us to engage members with precise data about their care while enabling empathetic and personalized experiences,” says Ardie Sameti, Accolade’s Senior Director of AI and Automation. “Gen AI solutions help us save significant time in after-call work and allow our front-line healthcare team to focus on building lasting relationships with every member we serve.”
Contact center leaders no longer have to struggle with slow, complex implementations and incomplete or inaccurate insights. With this release, Observe.AI enables contact centers to fully harness Gen AI to tailor conversation intelligence to their unique business requirements.
Realize immediate value today with Observe.AI. To learn how, request a demo.
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Observe.AI is used by 350+ enterprise customers including Accolade, Affordable Care, Concentrix, Cox Automotive, Maxor, Pearson, and Public Storage, and analyzes over 2 billion transactions to support 100s of thousands of agents. The platform is powered by the only contact center-specific 40-billion-parameter LLM, wrapped in secure, supervisory layers and fine-tuned with over 100 years of contact center data, driving accuracy lifts of 45% for dead-air detection, 35% for call summarization, and 33% for sentiment detection compared with generic models. The platform integrates across the contact center and business tech stack - CCaaS, CRM, BI, HRIS, Knowledge Base, and more.
