Field Demonstrations

Production-Validated Systems

Not mockups. Not theory. These are functioning AI workflow systems
tested under real-world conditions with edge case handling.

System Walkthroughs

Watch how operational drift correction works in practice

SaaS • Lead Qualification

AI Sales Engine for SaaS

Multi-source lead capture with AI-powered qualification, intent scoring, and instant routing. Handles 100+ leads/day with 2-minute response time.

15+
Hours Saved/Week
95%
Classification Accuracy
2 min
Response Time
Make.com OpenAI GPT-4 Slack API HubSpot
Agency • Content Automation

Content Repurposing Engine

Automated transcription, AI extraction of key insights, and platform-specific content generation. Turns 60-minute webinars into 20+ social posts.

8+
Hours Saved/Piece
Content Output
5
Platforms Covered
AssemblyAI GPT-4 n8n Buffer
E-commerce • Operations

Unified Operations Hub

Order tracking, customer support triage, inventory alerts, and automated follow-ups. Single control center for all operational workflows.

20+
Hours Saved/Week
0
Missed Requests
40%
Faster Resolution
Shopify API Claude AI Gmail Slack

Core Architecture Principles

How we prevent operational drift by design

🔍 Decision Logic Separation

Business logic is defined separately from workflow execution. Changes to "what qualifies a lead" don't require rebuilding the entire system.

✅ Edge Case Testing

Every system is tested with malformed inputs, API failures, rate limits, and duplicate data before deployment. No silent failures.

📊 Continuous Monitoring

Real-time alerts on decision accuracy, response times, and error rates. Monthly drift audits catch logic degradation early.

🔄 Idempotent Operations

All actions are safe to retry. Network failures don't create duplicate tasks or missed assignments.

🎯 Context-Aware AI

AI decisions include full context: lead source, message history, company data. Not just pattern matching on keywords.

Validation Methodology

How we prove systems work before deployment

Phase 1

Simulated Load Testing

50-100+ test scenarios including edge cases, malformed data, and API timeouts. System must handle all gracefully.

Phase 2

Real Data Validation

Run system against client's historical data. Measure classification accuracy, response time, and false positive rate.

Phase 3

Parallel Operation

System runs alongside manual process for 1-2 weeks. Compare decisions to validate logic before full deployment.

Ready for your own validated system?

We'll map your workflow and design a drift-resistant architecture in 15 minutes.

Book Discovery Call

Or email: logicprompt.ai@gmail.com