Cross-Mining
Automatic call summaries: the highlights of each conversation in just a few lines.
With generative AI, Cross-Mining summarizes your calls, emails, chats, and messages —including the reason, key points, commitments made, and next steps. Your advisors and quality teams can understand a conversation at a glance and know whether it’s worth listening to.
Read two lines instead of listening to seven minutes of audio again.
Each interaction is automatically summarized. Combined with sentiment analysis and key phrase detection, the summary makes it easy to determine whether a conversation is worth listening to and analyzing further.
Reason
Why the customer contacted customer service.
Key Points
Any important points that were discussed, including the client's mood or tone.
Commitments
What was promised to the customer to ensure continuity.
Next Action
Reminders, tasks to be completed, escalations to anticipate.
Ten Uses for Automatic Summarization in Contact Centers.
Time savings for advisors
Less time spent writing up reports after each call.
Service Continuity
The conversation history is immediately visible: the customer doesn't have to repeat themselves.
Compliance
Every interaction is documented, which facilitates audits in regulated industries.
Identifying Dissatisfied Customers
The summary can incorporate the client's mood, in addition tothe sentiment analysis.
Optimized Tracking
The actions to be taken are listed so that nothing is overlooked, even across multiple calls.
Continuing Education
Archived summaries become resources for counselors' online courses.
Priority Management
Calls that require urgent attention or escalation are flagged.
Trend Analysis
A useful foundation for identifying recurring problems and initiating corrective actions.
Marketing and sales
The needs expressed by customers help shape more targeted offers and messages.
Multilingual Support
Abstracts can be translated to facilitate collaboration between teams.
The language model of your choice, powered by Cross-Mining.
Connect GPT, Claude, Gemini, or your private LLM. Cross-Mining orchestrates prompts, structures summaries, and feeds them into Listener QM and CRM Dataviz, with controlled budgets and quotas.
See the connectors for generative AI and the analytics connectors.
“Supervisors’ time is now devoted to workshops, handling requests, and working on quality and service attitude.”
Canal+
Automatic Call Summaries: Your Questions.
How does the automatic call summary work?
The call is transcribed by the speech to text, and then a language model generates a structured summary: rationale, key points, commitments, and next steps. Chats, emails, and messages are summarized directly.
What AI models are used?
You choose: GPT, Claude, Gemini, or a private LLM, via generative AI connectors. Cross-Mining orchestrates the prompts and structures the outputs.
What is the purpose of quality summaries?
When combined with sentiment and key phrases, they make it possible to quickly identify conversations worth listening to, saving time for supervisors and evaluators in the Quality Monitoring.
Can the abstracts be translated?
Yes. The summary can be generated as part of the same workflow as the translation of interactions, directly in your teams’ language.
Other Speech Analytics features
Want to work with us?
Contact us
