What I offer: Design and deployment of end-to-end AI-powered call transcript analysis and quality assurance systems — replacing manual spot-checking of 2–3% of calls with automated analysis of 100% of recorded interactions, producing agent performance scorecards, compliance violation reports, and training action plans with specific transcript evidence.
Each engagement delivers a complete system including knowledge base construction, custom QA framework design, structured AI prompt engineering pipeline, transcript analysis and scoring, agent evaluation reports, and a prioritised training action plan — all generated automatically from call recordings.
Skills applied: AI prompt engineering · Call transcript analysis · Quality assurance automation · Knowledge base design · Claude AI · ChatGPT · Turboscribe · QA framework design · Agent performance evaluation · Compliance monitoring · No-code automation · Contact centre operations · BFSI compliance · Customer support operations · Training needs analysis
My differentiator: I bring two things to this service that most automation freelancers cannot — a compliance operations background and structured prompt engineering capability developed through my Executive Certificate in Support and Operations Automation and AI.
My 7+ years in Indian government operations and financial services — including financial analysis and credit assessment work at LIC Housing Finance and compliance-heavy programme management under Odisha Livelihood Mission — gives me a genuine understanding of what institutional compliance monitoring looks like from the operational side. I know what needs to be flagged, what evidence is required to support a finding, and how a management report needs to be structured for decision-makers to act on it.
I use that compliance instinct to design QA frameworks that reflect your actual regulatory and business obligations — not generic scoring rubrics. For Indian fintech and BFSI clients, this means frameworks built around RBI disclosure requirements, collection call standards, and consent verification. For e-commerce and SaaS, it means frameworks weighted toward retention signals, escalation protocols, and product knowledge gaps.
The system I have built uses Claude AI and ChatGPT for analysis, Turboscribe for transcription with speaker diarization, and a 4-stage prompt pipeline moving from framework generation through transcript analysis, scoring, and training recommendation.
Particularly relevant for Indian fintech, BFSI, e-commerce customer support, BPO and contact centres, and regulated sectors where call compliance is a recurring audit risk. Full case study with QA framework, prompt examples, and sample output available in portfolio. Response time within 24 hours.