From Stalled to Stellar
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Fintech

From Stalled to Stellar

PayStream AI

8 weeks project
73%
Cost Reduction
Monthly cloud spend decreased from $40K to $11K
-89%
False Positives
Dramatic improvement in detection accuracy
6 weeks
Time to Production
From stalled project to live system
$12M
Funding Raised
Series A secured post-launch

The Challenge

PayStream's AI-powered fraud detection system was burning $40K/month in cloud costs while generating excessive false positives. After 18 months of development, the system was still in 'perpetual beta' with no clear path to production. The founding team was considering shutting down.

Our Solution

Our Deep Dive Triage revealed critical issues: the model architecture was fundamentally sound, but data preprocessing was flawed and the inference pipeline was massively over-engineered. We provided a detailed Fix roadmap focusing on data quality improvements and infrastructure simplification. Post-triage acceleration included LLM reengineering using modern RAG techniques and cost-optimized deployment.

Results & Impact

73% reduction in cloud infrastructure costs

89% decrease in false positive rates

Production deployment achieved in 6 weeks

Series A funding secured at $12M valuation

Processing 2M+ transactions monthly

"Ding Ventures saved our company. Their triage was brutally honest—they told us exactly what was broken and gave us a clear path to fix it. Six weeks later, we were in production. Three months after that, we closed our Series A."

Marcus Chen
CEO, PayStream AI
AI TriageFraud DetectionCost OptimizationLLMFintech

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