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Agner
Axendi Analytix
Agner
Actionable insights into usage, incoming queries and workload levels to better manage customer support demand
AI-powered internal support analytics for contact center & BPO
Agner is Axendi’s proprietary system for analysis, monitoring, and optimization of internal support operations. It was developed to address real challenges in complex customer service environments, where knowledge and expertise are dispersed across multiple communication channels.
The system monitors internal consultations between agents on Microsoft Teams channels, providing both real-time visibility and structured data analysis. Agner aggregates interactions into clear summaries, reports, and dashboards, highlighting trends across skills, communication channels, and peak consultation hours.
This gives organizations a clear view of how internal support functions — where agents need assistance, which topics recur most often, and where knowledge gaps exist. Instead of fragmented conversations, companies gain a structured, data-driven understanding of internal expertise and support flows.
Agner supports both agents, by improving the quality of questions and knowledge exchange, and team leaders, by enabling more effective knowledge management and targeted training decisions.
How can you use it?
1
Real-time monitoring
Tracking internal support requests factors across communication channels.
2
Advanced analytics
Analyzing post volumes, question patterns, response times, and peak activity periods with customizable filters.
3
Performance optimization
Enabling detailed tracking of agent effectiveness, team metrics, and consultation patterns.
Why internal support visibility matters?
In complex customer service operations, internal consultations are a hidden but critical layer of performance. Every question asked between agents, every request for clarification, and every exception discussed internally reflects how well processes, knowledge, and training are working.
When this internal support layer is not visible, organizations struggle to understand where friction truly exists. Decisions about training, documentation, and process improvement are often based on assumptions rather than real operational signals.
Agner makes this internal knowledge flow measurable. By turning everyday consultations into structured insight, it allows companies to manage internal expertise with the same discipline they apply to customer-facing performance.
Business challenges Agner solves
1
Information scattered across channels
Internal support happens across chats, calls, and side conversations, making knowledge hard to find and impossible to analyze. Agner structures these interactions into searchable, actionable data.
2
No visibility into advisor struggles
Leaders often rely on assumptions, while real challenges appear in internal consultations. Agner exposes frequent questions, confusion areas, and skill gaps.
3
Difficulty identifying training needs
Training is often generic. Agner shows where support is most needed, enabling targeted, evidence-based training.
2
Onboarding challenges in growing teams
New advisors rely heavily on internal help. Agner highlights onboarding gaps and helps adjust training based on real operational questions.
Enhanced service quality
Quickly spot recurring issues, deliver targeted training, and boost response times—so your customer service keeps getting better.
Operational efficiency
Reduce costs, balance team workloads, and onboard new agents faster—so your operations run smoother and perform better.
Strategic insights
Use real-time data to spot peak hours, plan resources smarter, and solve issues before they impact service—so you stay ahead.
Where Agner delivers the most value
1
Large customer service operations
In complex service operations, advisors constantly consult each other about processes, case types, and exceptions. Knowledge becomes scattered and hard to manage. Agner reveals recurring questions, highlights knowledge gaps, and supports data-driven training and onboarding. Ideal for BPO providers, shared service centers, and in-house contact centers.
2
Regulated industries
In regulated environments, internal consultations often concern KYC and AML decisions, compliance interpretation, documentation standards, and exception handling — where inconsistent answers create real risk.
Agner detects patterns in compliance-related questions, highlights unclear procedures, and supports risk reduction and training based on real operational issues. Ideal for medical, banks, fintechs, insurers, and financial BPO operations.
Agner detects patterns in compliance-related questions, highlights unclear procedures, and supports risk reduction and training based on real operational issues. Ideal for medical, banks, fintechs, insurers, and financial BPO operations.
3
E-commerce and market paces
In fast-moving e-commerce operations, advisors frequently consult each other about orders, logistics exceptions, payments, disputes, and policy edge cases.
Agner shows where processes cause confusion, identifies pressure points and peak consultation times, and supports faster onboarding and more consistent answers — especially during peak seasons. Especially useful for marketplaces and large online retailers.
Agner shows where processes cause confusion, identifies pressure points and peak consultation times, and supports faster onboarding and more consistent answers — especially during peak seasons. Especially useful for marketplaces and large online retailers.
4
Organizations with multi-level support models
In multi- level support structures, internal expert consultations are constant but often invisible. Agner gives leaders visibility into escalation patterns, highlights frequently escalated topics, and provides data to improve knowledge bases and escalation flows.
Strong fit for IT support, technical helpdesks, and service desks.
Strong fit for IT support, technical helpdesks, and service desks.
Case study
Agner helped achieve +10pp in service quality
Axendi faced limitations with off-the-shelf analytical and monitoring tools while supporting Allegro’s e-commerce project. To boost agent performance and service quality, the New Tech team built a proprietary AI solution — Agner. It enabled real-time internal request analysis, centralized communication, and supported targeted training efforts. The result: +10pp in quality, 50% faster agent responses, and a 35% reduction in consultation time.
Why Agner?
Agner is inspired by Agner Krarup Erlang (1878–1929), a Danish mathematician and engineer who was a pioneer in telecommunications traffic theory and statistics.
His groundbreaking work on modeling traffic in telephone networks laid the foundation for modern queueing theory and efficient data flow management. The unit of telecommunications traffic, the erlang, was named in his honor.
Erlang is recognized as one of the founders of modern telecommunications, and his methods for analyzing and optimizing networks remain fundamental in IT and telecom industries. His legacy continues to inspire innovation in communication system design and resource management — the same principles that guide Agner’s approach to understanding and optimizing internal support flows.
Proven through experience.
Chosen for trust.
What challenges can Agner help solve?
- Inefficient consultation organization and lack of monitoring tools
- Limited access to critical service and product information
- Time-consuming internal support analysis requiring manual content searching
How does Agner improve customer service quality?
Our AI analytical customer service solution enables:
- Daily analysis of advisor and leader performance
- Data-driven training and workshop development
- Creation of accessible procedures based on real challenges
- Precise work scheduling based on peak hour analysis
- Proactive problem-solving through comprehensive data insights
What kind of analytics does Agner provide?
- Real-time monitoring of support requests
- Analysis of consultation patterns and response times
- Peak period identification
- Agent performance metrics
- Team efficiency indicators
- Custom reporting with multiple filters
