Customer Success StoryAI Voice Agents • Enterprise SaaS

MyOperator Achieved 4-6x AI Performance with Autonomous Optimization

How India's leading call center platform transformed their AI agents from unreliable to production-ready using Noveum's 24/7 autonomous optimization engine.

MyOperator processes millions of AI voice interactions monthly. Before Noveum, diagnosing failures was impossible. Now, their AI agents achieve 95%+ success rates—automatically optimized without human intervention.

Built for Enterprise
4-line SDK integration
Results in < 24 hours
"

We went from spending days debugging agent failures to having verified fixes delivered automatically. Noveum changed how we build AI.

Lead AI EngineerMyOperator
MyOperator Logo

India's #1 Cloud Call Center Platform

Verified Results
4-6x
Performance Improvement
200x
Faster Optimization
95%+
Success Rate Achieved
4 Lines of Codeto integrate
MyOperator Logo

MyOperator is India's #1 cloud-based call management system, trusted by 12,000+ businesses to power their customer communications with AI.

Cloud Call CenterAI Voice AgentsEnterprise SaaS
Customer Profile

India's Leading Business Communication Platform

Founded in 2013, MyOperator has grown to become the go-to platform for enterprise-grade AI-powered communication solutions. Their intelligent voice bots and AI agents handle millions of customer interactions daily, making them a perfect candidate for advanced AI observability.

Millions+
Monthly AI Interactions
100+
AI Voice Agents
50K+
Daily Calls Processed
12,000+
Enterprise Customers
The Problem

The Challenge: Flying Blind at Scale

MyOperator's AI agents were a core part of their business, but the engineering team faced a critical challenge: they were flying blind. With a massive volume of interactions, they had no efficient way to diagnose the root causes of agent failures.

Lack of Visibility

It was impossible to pinpoint why an agent failed from terabytes of logs.

Unscalable Manual Effort

Manually reviewing conversations and testing fixes was slow, inefficient, and couldn't keep up with the volume.

Inability to Catch Subtle Failures

Nuanced issues like agent hallucinations or persona drift were nearly impossible for human engineers to detect at scale.

"

Our customers would report an issue, and we'd be lost. We had the data, but we couldn't turn it into answers. We were spending more time searching for problems than solving them.

Lead AI Engineer, MyOperator
The Solution

Under the Hood: The 24/7 Continuous Optimization Pipeline

Noveum.ai's platform is more than a tool; it's a perpetual, autonomous quality assurance and optimization engine that runs 24/7.

Running 24/7
1
Real-Time Trace Collection
2
Automated ETL & Dataset Enrichment
3
Continuous Evaluation with 20+ Scorers
4
NovaPilot Analysis & Root Cause Identification
5
Evolutionary Auto-Fix & Simulation
6
Delivery of Verified Fixes
Step 6Step 1
Continuous improvement cycle
1
Real-Time Trace Collection

After a simple 4-line-of-code integration with MyOperator's LangChain setup, the Noveum.ai platform began to passively collect raw production traces from every agent interaction, without impacting performance.

2
Automated ETL & Dataset Enrichment

A sophisticated ETL (Extract, Transform, Load) job runs continuously, transforming the raw, unstructured traces into clean, structured dataset items. This process enriches the data, making it ready for deep analysis.

3
Continuous Evaluation with 20+ Scorers

As new dataset items are created, they are immediately evaluated against Noveum.ai's suite of 20+ specialized scorers. These scorers, covering everything from Factual Accuracy to Role Adherence, provide a multi-dimensional, quantitative assessment of every single interaction.

4
NovaPilot Analysis & Root Cause Identification

NovaPilot, Noveum.ai's own agent, analyzes the firehose of scored data in real-time. It identifies patterns, clusters failures, and performs a root cause analysis to pinpoint the underlying issues that are causing poor performance.

5
Evolutionary Auto-Fix & Simulation

Based on its analysis, NovaPilot generates hundreds of potential fixes (e.g., system prompt modifications). It then initiates an evolutionary optimization process, running simulations to test these fixes across multiple generations.

6
Delivery of Verified Fixes

The 'winning' prompt—the one that is mathematically proven to deliver the highest performance—is then delivered to the engineering team, ready for deployment. This entire cycle, from collecting a trace to having a verified fix, runs continuously, 24/7, without any human intervention.

This 'Set It and Forget It' pipeline transformed MyOperator's reactive, manual process into a proactive, autonomous, and perpetual improvement loop.

Evolutionary AI

Evolutionary Optimization: Natural Selection for AI Prompts

Like biological evolution, NovaPilot tests hundreds of potential fixes across multiple generations. The best performers survive and combine, while poor performers are discarded—delivering mathematically proven improvements.

How Evolutionary Optimization Works

Generate
Create 100+ prompt variations
Simulate
Test each against real data
Evaluate
Score with 20+ metrics
Evolve
Keep winners, combine traits

Multi-Generation Selection Process

Generation 1
100
fixes tested
75
Generation 2
25
fixes tested
17
Generation 3
8
fixes tested
5
Final
3
fixes tested
Verified Winner Emerges — Ready for Production

Without Evolutionary Optimization

  • Manual A/B testing takes weeks
  • Only 2-3 variations tested at a time
  • No guarantee of optimal solution
  • Human bias influences prompt selection

With NovaPilot's Evolutionary Engine

  • Automated testing completes in minutes
  • 100+ variations tested per generation
  • Mathematically proven optimal prompt
  • Data-driven selection, no human bias

The evolutionary process doesn't just find good solutions—it finds the best possible solution by exploring the entire solution space automatically.

Technical Deep Dive

Complete List of AI-Generated Fixes

NovaPilot tested hundreds of prompt variations across 4 generations. Here are the top 5 verified fixes that delivered the most significant improvements, along with their measured impact:

136+
Prompt Variations Tested
4
Evolution Generations
5
Verified Winning Fixes
10min
Minutes to Optimize

Top 5 Verified Winning Fixes

1

Fixing Critical Hallucinations

explicit_domain_scope_constraint
Problem Detected

The agent was inventing features and omitting critical data, causing users to receive incorrect information about product capabilities.

NovaPilot's AI-Generated Fix

Introduced a strict domain scope constraint that explicitly defines boundaries and politely redirects out-of-scope questions.

Verified Results
Hallucination Detection
2.8/109.5/10+6.7
Role Adherence
2.5/109.2/10+6.7
2

Strengthening Agent Identity

simplify_and_focus_identity_statement
Problem Detected

The agent was confused about its own identity and persona, leading to inconsistent and confusing responses.

NovaPilot's AI-Generated Fix

Implemented a simplified, focused identity statement that clearly defines the agent's role and personality.

Verified Results
Role Adherence
2.2/109.2/10+7.0
Q&A Alignment
1.1/109.5/10+8.4
3

Clarifying SaaS Context

clarify_heyo_context_as_saas_platform
Problem Detected

The agent didn't understand it was representing a SaaS platform, leading to incorrect assumptions about product delivery and support.

NovaPilot's AI-Generated Fix

Added explicit SaaS platform context, clarifying that Heyo is a cloud-based service with online support and self-service features.

Verified Results
Role Adherence
2.2/109.2/10+7.0
Q&A Alignment
1.0/109.5/10+8.5
4

Amplifying Domain Constraints

amplify_domain_constraint_with_examples
Problem Detected

The agent was still occasionally answering out-of-scope questions, especially edge cases not covered by the original constraints.

NovaPilot's AI-Generated Fix

Added concrete examples of in-scope vs out-of-scope questions to the domain constraint, making boundaries crystal clear.

Verified Results
Hallucination Detection
3.8/109.5/10+5.7
Role Adherence
3.0/109.5/10+6.5
5

Enforcing Truthfulness

truth_first_constraint_and_unknown_response
Problem Detected

The agent would sometimes guess instead of admitting it didn't know, leading to confident but incorrect answers.

NovaPilot's AI-Generated Fix

Implemented a 'truth-first' constraint that prioritizes accuracy over helpfulness, with a graceful unknown response template.

Verified Results
Q&A Alignment
0.9/109.5/10+8.6
Role Adherence
2.5/109.2/10+6.7

Additional Behavioral Fixes

Beyond the core optimizations, NovaPilot also identified and fixed these behavioral issues:

Problem

The agent was making up its own follow-up questions, leading to inconsistent user experiences.

NovaPilot's Fix

Added a new critical rule: THE 'NO IMPROV' RULE (CRITICAL), strictly forbidding the agent from improvising questions.

Problem

The agent was confused about its own identity, sometimes referring to itself as a 'bot' or 'agent.'

NovaPilot's Fix

Strengthened the persona rule: You must never reveal you are a bot. You are a human specialist named Riva.

Problem

The agent would try to access user account details, which it couldn't do, leading to a frustrating dead-end for the user.

NovaPilot's Fix

Added a NO-API guardrail, explicitly stating that it cannot check a user's status and providing a clear escalation path.

Problem

Users with complex issues had no clear path to human support, causing frustration and abandoned conversations.

NovaPilot's Fix

Implemented a smart escalation protocol that detects frustration signals and proactively offers human agent handoff.

What Didn't Work: Failed Experiments

Not every AI-generated fix succeeded. Here's what NovaPilot learned from its failures:

remove_hedging_from_domain_scope

Removed helpful examples from the prompt, intending to make it more direct and concise.

-4.7 score drop
add_verbose_context_explanation

Added lengthy explanations about the product to help the agent understand context better.

-2.3 score drop
strict_one_sentence_responses

Forced all responses to be single sentences for brevity.

-3.1 score drop
Why Failures Matter

These failures are actually valuable—they prove the evolutionary process works. NovaPilot automatically discards changes that hurt performance, ensuring only verified improvements make it to production.

The Results

Verified Performance and a Paradigm Shift

The cumulative effect of all the AI-generated improvements resulted in a massive overall performance gain:

MetricBeforeAfter (Verified)Improvement
Context Relevancy1.47/108.5/105.8x
Role Adherence1.99/108.5/104.3x
Overall Success Rate84%95%++11%

The Business Transformation

20-30%
Reduction in AI Engineering Overhead

Freed up expensive engineering resources from manual debugging.

200x
Faster Workflow

Shortened the feedback loop from weeks to minutes.

Scale with Confidence

Enabled the team to manage hundreds of agents without a linear increase in team size.

Why Noveum.ai?

The Complete Solution

MyOperator chose Noveum.ai because it offered a complete, end-to-end solution that went beyond simple monitoring.

Fully Autonomous Engine

NovaPilot handled the entire quality assurance lifecycle, 24/7, without human intervention.

Verifiable, Data-Driven Results

The evolutionary process didn't just suggest fixes; it proved them with data through rigorous simulation.

Unprecedented Speed and Agility

The 10-minute optimization cycle was a game-changer, enabling rapid iteration and continuous improvement.

Conclusion

The partnership between MyOperator and Noveum.ai proves a fundamental truth of the modern AI stack: you cannot afford to fly blind. The challenge of ensuring quality at scale is a machine-scale problem that requires a machine-scale solution.

Noveum.ai, with its 15-minute integration and the 24/7 autonomous, evolutionary capabilities of NovaPilot, provides that solution. It is an essential platform for any enterprise that is serious about deploying reliable, high-performing AI agents.

Ready to Transform Your AI Operations?

Stop Flying Blind

See how Noveum.ai can help you automate your AI quality assurance and unlock the full potential of your agents.