Not mockups. Not theory. These are functioning AI workflow systems
tested under real-world conditions with edge case handling.
Watch how operational drift correction works in practice
Multi-source lead capture with AI-powered qualification, intent scoring, and instant routing. Handles 100+ leads/day with 2-minute response time.
Lead intake, client reporting, and cross-platform data syncing handled by a multi-node AI workflow. Built to reclaim 30+ hours per week from repetitive agency operations.
Google Sheets or Shopify events route customers into the right action path: purchase confirmation, abandoned-cart recovery, and automated action logging.
Click any node to see the tool and logic. Hit Run to watch data flow live.
How we prevent operational drift by design
Business logic is defined separately from workflow execution. Changes to "what qualifies a lead" don't require rebuilding the entire system.
Every system is tested with malformed inputs, API failures, rate limits, and duplicate data before deployment. No silent failures.
Real-time alerts on decision accuracy, response times, and error rates. Monthly drift audits catch logic degradation early.
All actions are safe to retry. Network failures don't create duplicate tasks or missed assignments.
AI decisions include full context: lead source, message history, company data. Not just pattern matching on keywords.
How we prove systems work before deployment
50-100+ test scenarios including edge cases, malformed data, and API timeouts. System must handle all gracefully.
Run system against client's historical data. Measure classification accuracy, response time, and false positive rate.
System runs alongside manual process for 1-2 weeks. Compare decisions to validate logic before full deployment.
We'll map your workflow and design a drift-resistant architecture in 15 minutes.
Book Discovery CallOr email: logicprompt.ai@gmail.com