Public Case Study
AI-Powered Call Analytics on AWS
Client Overview
Client
Industry
Use Case
Platform
Implementing Partner
Client Overview
Client
Industry
Use Case
Platform
Implementing Partner
Executive Summary
Lakshmishree’s team used to manually listen to a small sample of call recordings — typically 5–10% — and score them using subjective criteria that varied across reviewers. This process took 24–48 hours per review cycle and left the majority of calls unanalyzed, with compliance violations going undetected until customer complaints surfaced. Management had no visibility into Relationship Manager (RM) performance, no consistent scoring framework, and no way to provide targeted coaching.
Infimatrix Technologies deployed a fully serverless, AI-powered call analytics pipeline on AWS using Amazon Bedrock, Amazon Transcribe, Amazon Transcribe Call Analytics, and Amazon Comprehend. The solution automatically transcribes, analyses, and processes 100% of customer calls within minutes of ingestion — producing call summaries, sentiment analysis, customer issue identification, resolution status, agent performance assessments, and action items — delivered through interactive Amazon QuickSight dashboards accessible to management at RM-level, branch-level, and network-wide views. The entire solution is deployed in a dedicated AWS Region to meet data residency requirements, with S3 encryption at rest, CloudTrail audit logging, and cross-account secure ingestion.
The Challenge
Manual, Inconsistent Call Reviews
Only a small sample of calls were reviewed manually. Subjective scoring varied across reviewers, providing no reliable quality baseline.
No RM Performance Visibility
Management had no systematic way to track RM performance in pitching, objection handling, or script adherence across branches.
Invisible Coaching Gaps
Training needs and skill gaps were invisible - no data to identify which RMs needed coaching or on which specific areas.
No Call Quality-Outcome Correlation
No way to correlate call quality with conversion rates, activations, or customer retention — good calls were indistinguishable from poor ones.
PII Exposure Risk
Sensitive customer data (PAN, Aadhaar, account numbers) shared on calls posed regulatory risk with no detection mechanism in place.
Compliance ViolationsUndetected
Unauthorized promises, missing risk disclosures, and regulatory violations went unnoticed until customer complaints surfaced.
No Consistent Scoring Framework
No standardized, objective scoring rubric was applied uniformly across all RMs and branches — subjective assessments varied by reviewer.
The Solution
Infimatrix Technologies implemented a fully serverless, event-driven call analytics pipeline on AWS. The solution is deployed within a dedicated AWS Region, secured with S3 server-side encryption (SSE-S3), cross-account secure ingestion with IAM dual-authorisation, and full observability through Amazon CloudWatch and AWS CloudTrail.
Every call recording is automatically ingested, transcribed, analysed, and processed within minutes. A scheduled ingestion process retrieves recordings from the telephony provider, and the pipeline handles each call individually through the multi-stage AI processing workflow.
Business Outcomes
KPI
Before
After
How Measured
Call Quality Review Coverage
5–10% of calls manually reviewed
100% of calls automatically analyzed
Pipeline processing logs
Time to Generate Call Insights
24–48 days per manual review cycle
Under 5 minutes per call
Step Functions execution metrics
Compliance Violation Detection
Reactive — detected only after customer complaints
Proactive — issues surfaced through structured per-call analysis
Bedrock structured output analysis
RM Scoring Consistency
Subjective — varied across reviewers
Objective — standardised AI-driven analysis with consistent structure
Consistent per-call output structure
Management Visibility
No dashboards or reporting
Real-time interactive QuickSight dashboards
Dashboard adoption and usage metrics
Structured Agent Analysis
Ad-hoc, generic feedback
Per-call structured analysis with agent performance assessment and action items
Per-call structured output review
PII Compliance
No detection or redaction mechanism
Automatic PII detection and redaction
Comprehend PII detection logs
Post-deployment, the solution delivered the following outcomes across call quality management operations at Lakshmishree Investment & Securities:
Post-deployment, the solution delivered the following outcomes across call quality management operations at Lakshmishree Investment & Securities:
Key Benefits
- Data-Driven Decision Making : Enables correlation between call quality scores and business outcomes such as conversion rates, customer retention, and revenue per RM — turning call data into strategic intelligence.
- Scalable & Serverless Architecture : Fully serverless pipeline handles any call volume — from hundreds to thousands of calls per day — with zero infrastructure management and automatic scaling.
- Security & Regulatory Compliance : Deployed in a dedicated AWS Region for data residency, with S3 encryption at rest, CloudTrail audit logging, and IAM-based access control — meeting SEBI regulatory requirements.
- Reduced Operational Overhead : Eliminates the manual review bottleneck entirely, freeing the quality team to focus on strategic coaching and compliance improvement rather than call sampling.
- Future-Ready Platform : Architecture supports adding new languages, CRM integrations, and additional analytics modules without re-engineering the core pipeline.
- Data-Driven Decision Making : Enables correlation between call quality scores and business outcomes such as conversion rates, customer retention, and revenue per RM — turning call data into strategic intelligence.
- Scalable & Serverless Architecture : Fully serverless pipeline handles any call volume — from hundreds to thousands of calls per day — with zero infrastructure management and automatic scaling.
- Security & Regulatory Compliance : Deployed in a dedicated AWS Region for data residency, with S3 encryption at rest, CloudTrail audit logging, and IAM-based access control — meeting SEBI regulatory requirements.
- Reduced Operational Overhead : Eliminates the manual review bottleneck entirely, freeing the quality team to focus on strategic coaching and compliance improvement rather than call sampling.
- Future-Ready Platform : Architecture supports adding new languages, CRM integrations, and additional analytics modules without re-engineering the core pipeline.
Conclusion
Infimatrix Technologies successfully deployed a secure, enterprise-grade AI-powered call analytics pipeline for Lakshmishree Investment & Securities on AWS, built on three core pillars:
Security-First Design
Cross-account secure ingestion with IAM dual-authorisation, S3 encryption at rest, deployment in a dedicated AWS Region for data residency, and a full audit trail via AWS CloudTrail — meeting SEBI and financial services regulatory requirements.
100% Automated Coverage & Data-Driven Coaching
Manual, sample-based reviews have been fully replaced by automated analysis of 100% of calls. Structured per-call analysis gives management and team leads the tools to develop RM performance at scale, with data rather than intuition.
Generative AI at Scale
Amazon Bedrock (Nova Pro) delivers multi-dimensional, per-call evaluation — call summarisation, sentiment analysis, customer issue identification, resolution status, agent performance assessment, and action items extraction — automatically, for every call.
This fully managed, serverless solution is applicable to any BFSI organisation seeking to modernise call quality management, strengthen compliance posture, and develop their advisor workforce through data-driven insights.
Conclusion
Infimatrix Technologies successfully deployed a secure, enterprise-grade AI-powered call analytics pipeline for Lakshmishree Investment & Securities on AWS, built on three core pillars:
Security-First Design
Cross-account secure ingestion with IAM dual-authorisation, S3 encryption at rest, deployment in a dedicated AWS Region for data residency, and a full audit trail via AWS CloudTrail — meeting SEBI and financial services regulatory requirements.
100% Automated Coverage & Data-Driven Coaching
Manual, sample-based reviews have been fully replaced by automated analysis of 100% of calls. Structured per-call analysis gives management and team leads the tools to develop RM performance at scale, with data rather than intuition.
Generative AI at Scale
Amazon Bedrock (Nova Pro) delivers multi-dimensional, per-call evaluation — call summarisation, sentiment analysis, customer issue identification, resolution status, agent performance assessment, and action items extraction — automatically, for every call.
This fully managed, serverless solution is applicable to any BFSI organisation seeking to modernise call quality management, strengthen compliance posture, and develop their advisor workforce through data-driven insights.
About Infimatrix
Infimatrix Technologies Pvt. Ltd. is an AWS Partner specialising in Generative AI, cloud-native architecture, and digital transformation for regulated industries
Generative AI
Amazon Bedrock
Call Analytics
RAG Solutions
AWS Solutions
BFSI Digital Transformation
About Infimatrix
Infimatrix Technologies Pvt. Ltd. is an AWS Partner specialising in Generative AI, cloud-native architecture, and digital transformation for regulated industries.