Ask AI anything about your meetings
Stop watching recording after recording, after recording… Get data insights from multiple meetings at once and take productivity gains to an entire new level.
Wait, what was his cat's name?
No more skipping back and forth in your recording. Ask tl;dv pretty much anything about your meeting and get your answer in a split second.
Uncover the insights that matter
AI analytics gives valuable meeting insights. Spot discussion trends and important points easily, making your talks a powerful tool.
Susana de Sousa
CS Director, Loom
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Reports on autopilot. Set and forget.
Choose your meetings, set a schedule, and let AI highlight important insights and trends, delivering them right when you need them for smart decisions.
Empower everyone in your team to be high-performers – with personalized scorecards to improve their skills and see how everyone’s doing, plus guides to handle tough questions easily,
Your questions, explained
What is Conversational Intelligence
Conversational intelligence from a meetings perspective refers to the use of AI technologies to analyze and interpret the content and dynamics of conversations that occur during meetings.
This advanced application of AI seeks to understand, process, and provide insights into the verbal and non-verbal communication that takes place, with the goal of improving meeting outcomes, participant engagement, and overall communication effectiveness.
Here are the key components and benefits of conversational intelligence in the context of meetings:
Key Components
Speech Recognition: The ability to accurately transcribe spoken words into text, which is foundational for further analysis of the conversation.
Natural Language Processing (NLP): Enables the AI to understand the context, sentiments, and intent behind the spoken words, going beyond mere transcription to interpret the meaning of conversations.
Sentiment Analysis: Assesses the tone and emotional content of the conversation, identifying positive, negative, or neutral sentiments expressed by participants.
Topic and Keyword Detection: Identifies the main subjects discussed, recurring themes, and specific keywords that emerge during the meeting, helping to capture the focal points of the conversation.
Participant Engagement Analysis: Analyzes the participation rate of meeting attendees, including who speaks most often, who contributes ideas, and potentially who is disengaged or silent.
What are the benefits of Conversational Intelligence?
Analysing meetings for the purpose of conversational intelligence can have several benefits, from aggregating content across meetings, surface trends and insights from multiple meetings, enhance strategic decision making, facilitating knowledge sharing and innovation and ensuring continuity and accountability.
Aggregating Content Across Meetings
Centralized Knowledge Base: Conversational intelligence can compile and analyze the content of discussions from various meetings, creating a centralized repository of knowledge. This allows organizations to easily access and review discussions on specific topics, decisions made, and action items assigned over time.
Cross-meeting Analysis: By examining conversations across a series of meetings, AI can identify recurring themes, questions, or concerns, providing a broader understanding of ongoing challenges or areas of interest within the organization.
Identifying Trends and Patterns
Trend Detection: Conversational intelligence tools can detect trends in discussions, such as the increasing prominence of certain topics, shifts in sentiment regarding projects or policies, and emerging challenges or opportunities. This helps organizations to proactively address issues or capitalize on new ideas.
Pattern Recognition: AI algorithms can recognize patterns in how certain topics are discussed or resolved, offering insights into effective strategies or highlighting areas where the organization consistently struggles or excels.
Enhancing Strategic Decision-making
Data-driven Insights: The ability to analyze discussions over time equips leaders with data-driven insights into the organization’s operations, employee concerns, and market opportunities. This supports more informed strategic planning and decision-making.
Predictive Analysis: By understanding past discussions and outcomes, conversational intelligence can predict future trends, potential roadblocks, and areas requiring attention. This foresight allows organizations to prepare and strategize effectively.
Facilitating Knowledge Sharing and Innovation
Knowledge Sharing: Conversational intelligence can surface insights or ideas from one team or department that could benefit others, facilitating cross-functional knowledge sharing and collaboration.
Innovation Triggers: By aggregating and analyzing diverse viewpoints and discussions, AI can highlight unique ideas or innovative solutions that might otherwise be overlooked. This can be a catalyst for innovation and creative problem-solving across the organization.
Ensuring Continuity and Accountability
Tracking Decisions and Outcomes: Conversational intelligence provides a historical record of decisions made and actions agreed upon, ensuring accountability and continuity in projects and initiatives. This is particularly valuable in tracking the implementation and impact of decisions over time.
Action Item Follow-up: With AI’s ability to extract and summarize action items across meetings, teams can better track progress on tasks, ensuring that nothing falls through the cracks and that projects move forward as planned.
How to find insights with conversation intelligence
Conversation intelligence helps businesses extract actionable insights from meetings and customer interactions by automatically transcribing, analyzing, and summarizing key points. Using AI-powered tools like tl;dv, teams can:
- Identify trends & pain points in customer calls and internal meetings.
- Track key decisions & action items without manual note-taking.
- Spot coaching opportunities for sales and support teams.
- Enhance collaboration by sharing searchable, timestamped meeting highlights.
By leveraging AI-driven meeting insights, businesses can make data-backed decisions, improve efficiency, and boost overall productivity.
The importance of conversation intelligence in sales
Conversation intelligence is a game-changer for sales teams, helping reps close more deals by analyzing customer interactions in real time. With AI-driven tools like tl;dv, sales teams can:
- Uncover buyer intent by tracking objections, pain points, and engagement signals.
- Improve sales coaching with automated call analysis and feedback.
- Optimize messaging by identifying which pitches and responses drive conversions.
- Save time on note-taking with AI-powered meeting transcription and summaries.
By leveraging conversation intelligence, sales teams can refine their strategy, personalize outreach, and accelerate revenue growth.
How conversation intelligence enhances customer experience
Conversation intelligence transforms customer interactions by making them more personalized, efficient, and insightful. AI-powered tools like tl;dv help businesses:
- Understand customer needs by analyzing conversations for trends and feedback.
- Improve response times with AI-driven summaries and action item tracking.
- Ensure consistency in messaging across sales, support, and customer success teams.
- Enhance product & service improvements by surfacing recurring customer pain points.
By leveraging conversation intelligence, businesses can proactively address concerns, build stronger relationships, and deliver a seamless customer experience.
Conversation intelligence best practices
To get the most value from conversation intelligence, businesses should follow these best practices:
- Leverage AI-powered transcription & summaries – Automate note-taking in meetings to capture key insights without distraction.
- Analyze trends & patterns – Use conversation intelligence to identify recurring customer needs, objections, and opportunities.
- Align teams with shared insights – Ensure sales, customer support, and product teams access key conversation highlights to improve collaboration.
- Use real-time coaching & feedback – Train teams with AI-driven conversation analysis to refine messaging and responses.
- Act on data-driven insights – Turn conversation intelligence into action by optimizing sales pitches, improving customer support, and enhancing product offerings.
By integrating these best practices, businesses can maximize the impact of conversation intelligence and drive better decision-making.
Choosing the right conversation intelligence tool
Selecting the best conversation intelligence tool depends on your business needs. Here are key factors to consider:
- AI-powered transcription & analysis – Look for accurate, real-time transcription with AI-driven insights.
- Integration with your workflow – Ensure compatibility with tools like Zoom, Google Meet, CRM systems, and collaboration platforms.
- Searchable & shareable insights – Opt for a tool that lets you quickly find and share key moments from conversations.
- Scalability & ease of use – Choose a user-friendly platform that can scale with your team’s growth.
- Security & compliance – Ensure the tool meets data privacy regulations like GDPR and SOC 2.
- Automated summaries & action items – AI-powered meeting notes help teams stay aligned and take action faster.
A tool like tl;dv checks all these boxes, making it easy to capture, analyze, and act on business conversations.
