How We Built a Gong Competitor for $400 in 3 Days Using AI-Assisted Development

Published: January 2026 | Read time: 8 minutes

We built Callzeno, a conversation intelligence platform that competes with Gong and Chorus, in 3 days for $400 in API costs. Here's exactly how we did it.

The Challenge

Sales teams need to analyze hundreds of calls without listening to hours of recordings. Existing solutions like Gong and Chorus charge $100+/user/month with annual contracts—putting them out of reach for small and mid-size businesses.

We saw an opportunity: Could we build a similar platform using modern AI tools, dramatically cutting both development time and cost?

The Traditional Approach

Building a conversation intelligence platform traditionally requires:

• Team: 5-8 engineers (backend, frontend, ML, DevOps)
• Timeline: 4-6 months to MVP
• Cost: $150,000-$300,000+ in development costs
• Complexity: Custom transcription, NLP models, infrastructure scaling

Our Approach: AI-Assisted Development

Instead of traditional development, we used Cursor—an AI-powered code editor that acts like having a senior developer pair programming with you 24/7.

Our timeline:

• Day 1-2: Core architecture, database schema, file upload handling
• Day 2: OpenAI GPT-5.2 integration for transcription and analysis
• Day 3: User dashboard, background workers, deployment

Total development cost: $400 in OpenAI API calls for testing

The Tech Stack

• Backend: Node.js with Express
• Database: PostgreSQL 14
• Queue System: Background workers for async processing
• AI: OpenAI GPT-5.2 for transcription and conversation analysis
• Frontend: Next.js with Tailwind CSS
• Deployment: Containerized for easy scaling

What Callzeno Actually Does

Upload a sales call recording and Callzeno automatically:

1. Transcribes the entire conversation with speaker diarization
2. Analyzes the content for key moments, objections, and sentiment
3. Scores agent performance on communication, rapport, and close technique
4. Extracts action items, follow-ups, and competitive mentions
5. Answers custom questions about compliance or quality checks

Processing time: 2-5 minutes per call, regardless of length.

The Integration Challenge: 3 Methods in 3 Hours

After launching the core platform, we needed multiple ways for customers to upload recordings. Traditional approach: hire a backend developer for a week.

Our approach: 3 hours with Cursor.

We built three different integration methods:

1. REST API with authentication and presigned URLs (1 hour)
2. FTP/SFTP server with per-company credentials (1 hour)
3. Google Cloud Storage auto-sync with service accounts (1 hour)

Total cost: $0 (already had Cursor subscription)

Customers can now upload recordings via API, FTP, GCS auto-sync, or dashboard drag-and-drop.

Real-World Performance

Callzeno isn't a demo—it's a production system with paying customers:

• Processing capacity: 1,000+ calls per minute (tested and achieved)
• Analysis quality: Competitive with Gong/Chorus
• Cost per call: ~$0.40 in OpenAI API costs
• Pricing: $1/call or $120/user/month
• Customers: Moving companies, insurance agencies, call centers

The Hard Problems We Solved

1. API Timeouts

Long calls (30+ minutes) would timeout OpenAI's API. Solution: Chunk processing with automatic retry logic and progress tracking.

2. Rate Limiting

OpenAI has strict rate limits. Solution: Intelligent queue management with priority routing and adaptive throttling based on API response headers.

3. Cost Optimization

At scale, API costs add up. Solution: Batch similar requests, cache common analyses, and use prompt engineering to minimize token usage. Result: $0.40/call average including transcription and analysis.

4. Database Performance

High-volume concurrent writes slowed down at scale. Solution: Optimized indexes, batch inserts, and background worker pools. Now handles 1,000+ simultaneous uploads.

5. Real-Time Updates

Users want to see progress as calls process. Solution: WebSocket connections with job status streaming and completion notifications.

The Custom Questions Feature

One of Callzeno's most powerful features emerged almost accidentally: customers can ask custom compliance questions that get answered automatically on every call.

Example for moving companies:

• "Did the agent ask if there were stairs?"
• "Was insurance explained?"
• "Did they mention binding estimate?"

The AI responds with context:

"No. The call was a brief post-pickup check-in and did not include home access/discovery questions such as stairs, elevator access, or floor level."

This turns Callzeno from a "nice to have" into compliance insurance—automatically verifying 100% of calls against any requirement.

What We Learned

AI-Assisted Development is Real

Cursor didn't just speed us up 2x or 3x—it enabled development that would have been impossible for a solo developer in any reasonable timeframe. The AI doesn't just autocomplete; it understands architecture, suggests optimizations, and catches bugs before they ship.

Start With the Queue

We initially tried processing uploads synchronously. Big mistake. Within hours of launch, we had 1,000+ recordings backed up. Switching to a queue-based architecture with background workers solved this immediately.

Separate Transcription from Analysis

Our first version did transcription and analysis in one API call. This was expensive and slow. Breaking it into two steps—transcribe once, analyze many times—cut costs by 40% and enabled new features like custom questions.

Logging is Everything

When processing hundreds of calls simultaneously, debugging is impossible without comprehensive logging. We log every API call, queue event, and error condition with full context. This has saved us countless hours.

Users Care About Speed

When we optimized from 8-minute to 2-minute analysis time, customer satisfaction jumped noticeably. In SaaS, perceived speed matters as much as actual capability.

The Economics

At $1/call or $120/user/month, here's how the unit economics work:

Per-call pricing:

• Revenue: $1.00
• OpenAI API cost: ~$0.40
• Infrastructure: ~$0.10
• Margin: ~$0.50 (50%)

Monthly subscription:

• Revenue: $120/user/month
• Average usage: ~100 calls/user/month
• Cost: ~$50 in API + infrastructure
• Margin: ~$70/user (58%)

These margins allow us to profitably undercut enterprise competitors while investing in rapid feature development.

Traditional vs AI-Assisted: The Comparison

What This Means for Your Business

If we can build a production SaaS platform that competes with $100M+ funded companies in 3 days for $400, what could we build for your business?

The same approach works for:

• Internal tools that eliminate manual processes
• Customer portals with AI-powered features
• Data analysis platforms that extract insights automatically
• Workflow automation that connects your existing systems
• Custom AI applications tailored to your industry

What used to cost $200K and take 6 months can now cost $15K and take 2 weeks.

Try Callzeno Yourself

We're offering 50 free call analyses to see the platform in action. No credit card required.

Start your free trial →

Or if you want to build something similar for your business, let's talk →

The Bottom Line

AI-assisted development isn't hype—it's a fundamental shift in how software gets built. We proved it by building a production system in 3 days that would have taken a traditional team 6 months and $300K.

The tools exist. The AI models are ready. The only question is: will you adapt fast enough to stay competitive?

We did. And we can help you do the same.

About the Author: Cory Siebler is the founder of Autonimate, an IT services and AI development company in South Florida. He's been building technology solutions for 38 years, starting with Wildcat! BBS at age 8. Callzeno is his latest proof that the best way to understand AI is to build with it.

Want to see what we can build for you? Contact Autonimate →