Conversation analytics is a technology that uses AI to analyse customer interactions such as calls, chats, and emails.​

It automatically transcribes conversations, detects topics, identifies patterns, and evaluates performance. This allows organisations to understand why customers are contacting them, how agents are handling interactions, and where improvements can be made.​

Instead of reviewing a small sample of conversations manually, conversation analytics enables teams to analyse 100% of interactions and make data-driven decisions.

Agent Assist is AI-powered software that supports agents during live customer interactions by analysing conversations in real time. 

As the conversation happens, the system processes the transcript and provides immediate, context-aware guidance. This can include suggesting next steps, surfacing relevant information, or reminding agents to follow required processes or mention key topics. 

Unlike traditional tools that only provide insights after a call, real-time agent assist helps agents take the right actions in the moment. This improves consistency, reduces missed opportunities, and supports better outcomes across sales and customer service interactions. 

Feelingstream is designed for organisations that manage high volumes of customer interactions, particularly in industries such as telecom, banking, insurance, utilities, and logistics. 

It is used by: 
> Contact centre and customer service managers who need visibility into performance and quality 
> Sales leaders who want to improve conversion rates and ensure consistent execution 
> Operations and business intelligence teams who analyse trends, identify issues, and drive improvements 
> Quality and training teams who monitor interactions and support agent development 

Typical use cases include improving sales performance, monitoring service quality, identifying why customers contact support, reducing avoidable contact, and supporting agents in real time during conversations.  

Conversation analytics helps organisations improve performance, efficiency, and decision-making. 

By analysing all customer interactions, teams gain a complete view of what is happening across operations. This enables faster identification of issues, better coaching, and more consistent execution. 

The result is improved service quality, reduced inefficiencies, and better business outcomes across sales and customer service. 

Feelingstream combines conversation analytics with real-time agent support. 

While many solutions focus only on analysing conversations after they happen, Feelingstream also helps improve interactions as they happen. This creates a direct link between insight and action. 

The solution is designed for organisations that need both visibility and the ability to improve performance at scale. 

Improving call centre performance requires both visibility into conversations and the ability to act on that insight. 

Feelingstream provides this through a combination of conversation analytics and real-time agent support. With Leadstream, you can analyse interactions across channels and identify performance gaps, trends, and missed opportunities. With Agent Assist, you can guide agents during live conversations to ensure the right actions are taken. 

This helps teams improve consistency, reduce errors, and drive better outcomes across all interactions. 

Feelingstream improves conversion rates by helping teams execute consistently and act at the right moment during conversations. 

Agent Assist provides real-time prompts and guidance, helping agents present offers, handle objections, and follow the right process. At the same time, conversation analytics reveals which behaviours and approaches lead to successful outcomes across your team. 

This combination reduces missed opportunities and enables organisations to scale what works across all sales interactions. 

Feelingstream enables you to analyse 100% of customer conversations through automated transcription and AI-powered analysis. 

All interactions are processed automatically, allowing you to identify contact reasons, measure performance, and detect trends across every conversation – not just a small sample. 

With Leadstream, you gain full visibility into what is happening across your customer interactions. This replaces manual quality assurance with a scalable, data-driven approach and ensures that no insights or opportunities are missed. 

Feelingstream analyses customer interactions across channels to identify the reasons behind customer contact. 

Using AI, it detects patterns in conversations and groups them into topics such as billing issues, service problems, or product inquiries. This creates a clear, structured view of customer demand. 

By understanding why customers are contacting you, you can prioritise improvements, address recurring issues, and improve overall service quality. 

Avoidable contact often occurs due to process gaps, unclear communication, or service issues. 

Feelingstream helps identify these patterns by analysing conversations at scale and highlighting recurring problems that drive unnecessary contact. This makes it possible to address root causes rather than just handling symptoms. 

By reducing avoidable contact, organisations can lower operational costs and improve customer experience. 

Feelingstream enables organisations to move from manual, sample-based quality assurance to automated analysis across all interactions. 

With features such as Automatic Quality Score, interactions can be evaluated consistently and at scale, without relying on manual reviews. This provides a more objective and complete view of performance across teams and individuals. 

Managers can identify trends, monitor quality, and focus coaching efforts where they have the most impact. 

Feelingstream provides automatic summaries that allow you to quickly understand what happened in each interaction. 

Instead of reviewing full transcripts or recordings, summaries highlight the key points, outcomes, and context of conversations. This makes it easier to review interactions at scale and identify important patterns. 

Combined with search and filtering, this allows teams to find and understand relevant conversations quickly. 

AI improves training by providing real examples of customer interactions and identifying where agents need support. 

Conversation analytics highlights patterns, performance gaps, and best practices, allowing teams to focus training on what matters most. At the same time, Agent Assist supports agents during live interactions, helping them apply what they have learned in real time. 

This reduces ramp-up time and improves performance more quickly. 

Post-call analytics focuses on analysing conversations after they have ended. It helps identify trends, evaluate performance, and support coaching. 

Real-time agent assist, on the other hand, works during the conversation. It helps agents take the right actions in the moment, when it matters most. 

The two approaches are complementary: conversation analytics helps you understand what happened, while real-time agent assist helps you improve what is happening right now. 

When evaluating conversation analytics software, key factors to consider include: 
>Ability to analyse 100% of interactions 
>Support for multiple communication channels 
>Real-time capabilities alongside post-interaction analysis 
>Clear and actionable insights 
>Integration with existing systems 
>Strong data security and compliance 

The most effective solutions combine insight with real-time action. 

Conversation analytics platforms can be GDPR compliant when they include appropriate data protection measures.

Feelingstream is designed for enterprise environments and includes features such as secure data handling, access control, and audit capabilities. The platform is also built in line with recognised security standards, including ISO 27001, supporting a structured and audited approach to information security.

These measures help organisations manage customer data responsibly and in line with regulatory requirements.

Read more about data security.

Feelingstream is designed to operate within European regulatory frameworks, including GDPR, and supports organisations preparing for the EU AI Act. 

For example, Automatic Quality Score is AI Act ready. The quality scoring model is transparent and designed to support organisations in meeting upcoming regulatory requirements. 

More broadly, the platform includes features that support compliance, such as role-based access control, audit trails, and secure data handling. Feelingstream continuously monitors regulatory developments to ensure the platform evolves in line with EU legal requirements.