Enterprise · Services · Retail
Customer relationship management system
A single customer profile, communication history and a managed deal cycle.
Value proposition
Every customer interaction lives in one profile: employees see the context, managers see the funnel and churn risk.
Challenge
Communication history sits in mailboxes and messengers, tasks get lost and deal probability is judged subjectively.
Who it is for
- Commercial units
- Service and account teams
- Sales managers
- Operations directors
Digital core
- Single customer profile (Customer 360)
- Cross-channel communication history
- Deal funnel and stages
- Tasks and reminders
- Segmentation and campaigns
- Sales and service reporting
Functional modules
- Accounts and contacts
- Deals and proposals
- Requests and tickets
- Tasks and calendar
- Communication channel integration
- Dashboards and reports
Architecture
- 01
Channels
- Employee workplace
- Mobile access
- Web forms and requests
- Email and telephony
- 02
Business logic
- Sales and service processes
- Assignment rules
- Service SLA
- Customer access rights
- 03
AI layer
- CRM Copilot
- Communication summaries
- Next-best-action
- Churn forecasting
- 04
Data
- Unified customer profile
- Interaction history
- Sales data mart
- Segments
TEQ Intelligence Layer
AI Intelligence Layer
- Customer 360Implemented
- Communication summariesAI module available
- Automated task creationAI module available
- Next-best-actionAI-ready
- Churn forecastingAI-ready
- Semantic searchAI module available
- CRM CopilotAI module available
The AI modules are built and connect to the solutions. They are not yet running in production at client sites — they are available for a pilot or a deployment project.
Pluggable agents
CRM Copilot
AI module availableBuilds the customer profile, summarises communications and suggests the next best action.
- Customer 360
- Communication summaries
- Task creation
- Semantic search
Commercial commitments are made by employees. The agent never messages customers without confirmation.
Analytics AI Agent
AI module availablePrepares analytical commentary on metrics, detects anomalies and drafts reports.
- Data mart queries
- Anomaly detection
- Scenario modelling
- Report draft
Every conclusion references its data source. Publishing a report requires confirmation.
IT Support Agent
AI-readyHandles routine user requests, drafts solutions from the knowledge base and routes incidents.
- Request classification
- Knowledge base search
- Solution draft
- Service Desk routing
Incident closure is confirmed by a support engineer.
How it works
A typical scenario: from event to confirmed result.
- 11The customer reaches out through any channel; the request lands in the profile.
- 22The copilot assembles context: history, open tasks, commitments.
- 33The employee receives a summary and a suggested next step.
- 44The employee confirms the action — a task or a reply is created.
- 55Funnel metrics and churn risk are updated in reporting.
Integrations
- ERP and accounting systems
- Telephony and contact centre
- Email services
- Service Desk
- BI platforms
Security
- Access control over customer data
- Audit logging of actions and exports
- Personal data transfer control
- On-premise or private cloud deployment
The human role
AI prepares summaries and next-step recommendations. Customer communication and commitments are confirmed by the employee.
In government, financial and security-related processes the final decision is confirmed by an authorised employee. AI analyses the data and prepares a recommendation.
Discuss deploying this solution
Describe the target perimeter — we will propose a survey, a pilot or a full project.