IOanyT (Own Product) (AWS Marketplace)
TheHeartbeat.ai: From Concept to AWS Marketplace in Record Time
How we built a production AI/ML SaaS platform that analyzes 100% of contact center calls in real-time—proving our ability to take AI products from 0→1.
Quick Facts
The Visibility Gap: 95% of Customer Calls Go Unanalyzed
Contact centers are drowning in customer interactions—but analyzing them manually is impossible.
The Problem
Traditional contact centers manually sample only 2-5% of calls for quality assurance. This creates a massive visibility gap:
- Blind Spots: 95%+ of customer interactions are never reviewed
- Inconsistent Quality: No way to monitor all agent performance systematically
- Lost Insights: Customer sentiment, feedback, and pain points buried in unanalyzed calls
- Manual Bottleneck: QA teams overwhelmed—45 minutes to review a single call
- Delayed Feedback: Agents receive coaching weeks after the interaction occurred
Real Impact
A 300-agent contact center handling 50 calls per agent per day generates 15,000 calls daily. At 2-3% sampling, they review only 300-450 calls—leaving 14,500+ interactions invisible.
TheHeartbeat.ai: 100% Call Coverage with AI-Powered Analytics
We built TheHeartbeat.ai as a production-ready AI/ML SaaS platform that analyzes every single call in real-time—transforming contact center operations through comprehensive AI-driven insights.
The Breakthrough: 100% Automated Analysis
Not samples. Not manual reviews. Every call—transcribed, analyzed, scored, and reported automatically. From 2-5% visibility to 100% visibility.
Speech-to-Text Processing
AWS Transcribe + Custom Models
- 45+ languages supported
- Speaker diarization (agent/customer separation)
- Real-time and batch processing
AI-Powered Analytics
NLP, Custom PyTorch Models
- Sentiment & emotion detection
- Automated quality scoring
- Topic & entity extraction
Real-Time Alerts & Dashboards
React, D3.js, WebSockets
- Critical issue flagging
- Agent performance leaderboards
- Coaching opportunity identification
Seamless Integrations
RESTful API, Cloud Connectors
- Google Drive, Dropbox, Box
- GCP compatibility
- RESTful API for custom integrations
Production-Grade AWS Architecture
TheHeartbeat.ai is built on AWS cloud infrastructure designed for scale, security, and reliability—ready for enterprise deployments.
Data Layer
AWS S3, RDS (PostgreSQL)
- • Audio storage with lifecycle policies
- • Metadata storage for structured data
- • Encryption at rest (AES-256)
- • VPC isolation for security
Scale: Millions of call minutes stored, queryable in milliseconds
AI/ML Processing Pipeline
SageMaker, Transcribe, Lambda
- • Fine-tuned BERT models for sentiment
- • Custom PyTorch emotion detection
- • SageMaker endpoints for real-time inference
- • Auto-scaling based on processing load
Scale: Process thousands of calls simultaneously
Application Layer
React, FastAPI, Redis
- • React 18 with TypeScript frontend
- • FastAPI high-performance backend
- • Redis caching for fast responses
- • Multi-tenant architecture
Scale: Thousands of concurrent users, sub-second responses
DevOps & Monitoring
CloudWatch, CodePipeline
- • GitHub Actions CI/CD
- • Multi-stage deployments
- • HIPAA-ready infrastructure
- • 99.9% uptime SLA
Scale: Zero-downtime deployments
Measurable Outcomes: 300-Agent Contact Center
We deployed TheHeartbeat.ai at a hospitality client's 300-agent contact center. The results were immediate and quantifiable.
Before TheHeartbeat
- ✗ Manual QA sampling: 2-3% of calls
- ✗ Average QA review time: 45 minutes/call
- ✗ Inconsistent quality scoring (subjective)
- ✗ Delayed feedback to agents: 1-2 weeks
- ✗ High QA team workload and burnout
After TheHeartbeat
- ✓ 100% call coverage: Every call analyzed
- ✓ Real-time insights: Scores in minutes
- ✓ 28% improvement in agent quality scores
- ✓ 15% increase in customer satisfaction
- ✓ 60% reduction in QA team hours
ROI Analysis
Cost Savings
- • QA Team: Reduced from 8 FTE to 3 FTE
- • Time to Insight: Weeks → Minutes
- • Coverage: 2-3% → 100% (50x increase)
Revenue Impact
- • 15% satisfaction increase → higher retention
- • 28% quality improvement → better resolutions
- • Data-driven coaching → faster ramp-up
Estimated Annual Value: $500K+ in cost savings and revenue improvement
Proof of End-to-End AI Product Development Capability
TheHeartbeat.ai isn't just a project—it's proof that IOanyT can build AI/ML products from concept to production to marketplace success.
0→1 Product Development
Took an idea to production-ready SaaS platform. Full ownership from vision to execution.
Production ML at Scale
Processing millions of call minutes in production. Real customer workloads, not demos or POCs.
AWS Marketplace Success
Listed on AWS Marketplace as production-ready SaaS. Enterprise procurement ready.
Measurable Business Outcomes
28% quality improvement, 15% satisfaction increase. Real customers, real results.
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