Sales
Captures client requests, agreements, next steps and owners; populates agreed CRM fields and creates follow-up tasks.
- CRM field map
- tracking lost commitments
- deal stage and next step
AI
AI Calls: call protocols, analytics and commitment tracking
Deploy AI Calls with transcription, call protocols, agreement monitoring and analytics, integrated with your CRM, phone system and security.
Our clients
Clients and partners
5 KPIset before pilot
cloud / on-premisedeployment chosen based on data and security policy
human-in-the-loopconfidence threshold determines where human review is needed
How recording becomes a verifiable action
AI Calls Deployment
Source
Telephony or meetingrecording, participants, time and identifier
Recognition
Transcript and rolesspeakers, terminology dictionary, timestamps
Business Rules
Protocol and controlcommitments, fields, quality category, confidence thresholds
Action
CRM, tasks and analyticsresult recording, verification queue, change audit
Three scenarios for different teams
One system uses shared recording and audit, but evaluation rules and results are tuned for departmental operations.
Contact center
Audits calls against quality standards, identifies root causes of deviations and creates a review queue for management.
- integration with telephony queues
- coverage of all agreed-upon sample set
- personal data masking
Project teams
Captures decisions, open questions, owners and deadlines; links protocol to projects and preserves agreement history.
- unified protocol template
- search meeting history
- tasks in project system
Security and Control
| System / layer | Scope of responsibility |
|---|---|
| Recording Source | Legal basis for recording, participant list, access and deletion policy. |
| Speech recognition and LLM | Choice of cloud or on-premise deployment, request log, terminology dictionary and restriction on provider training on client data if required by policy. |
| Analysis rules | Template and category versions, test sample, confidence thresholds and manual review queue. |
| CRM and project management systems | Minimal service account permissions, idempotent recording and change audit. |
| Data warehouse | Recording and transcript retention period, access isolation, data masking and controlled deletion. |
Assess where AI can deliver impact in your process
Solution Boundaries
A fit
- stable source of recordings exists and clear link between call and customer, queue or project
- team can define protocol fields, quality category or mandatory commitments
- historical sample exists for reference annotation and comparison with current process
Verify before launch
- noise, interruptions, voice overlap and rare terminology affect recognition accuracy
- we verify support for specific languages and telephony on your recordings and API, not with general promises
- model output does not replace employee decision where error impacts customer, money or obligations
Pilot on historical calls
-
01
Choose one process
For example, initial sales call or quality control for one contact center queue.
-
02
Build the standard
An expert marks up a sample: protocol fields, violations, commitments and expected actions.
-
03
Connect source and rules
Configure recognition, dictionary, result template and test integration.
-
04
Compare with current process
Calculate five KPIs, document error types and manual review costs.
-
05
Make a decision
Scale, adjust boundaries or stop implementation based on measurements.
Related experience
Related experience with corporate memory and quality control
Next step
Pilot AI Calls
Provide a representative anonymized sample of recordings and your current control template. We'll return with pilot boundaries, metrics and integration schema; pricing is determined after data and workflow verification.
- recording source
- gold-standard markup
- Baseline KPIs
- cloud or on-premise
Discuss solution: AI Calls: protocols, analytics and…
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