Deep dives into the systems we've built and the measurable results we've achieved.
A large fintech was drowning in alert noise — 4,000+ daily alerts, resolution time of 4.2 hours. We built ML-based alert correlation (87% noise reduction), LLM-powered incident reasoning, anomaly detection on 200+ microservices, and agentic auto-remediation. Resolution time dropped to 18 minutes, on-call pages down 91%.
Zero-leakage, domain-tuned LLaMA-3 70B processing 10M+ research documents. 70% reduction in query time, 94% domain accuracy, full GxP regulatory compliance.
Helping a client build a purpose-built AI platform for MRO workflows — real-time visual inspection on edge hardware, predictive maintenance models, and intelligent repair automation. 96.8% anomaly detection accuracy, 40% reduction in unplanned downtime.
LangGraph-based multi-agent system automating regulatory reporting, risk scoring, and portfolio analysis. 60% reduction in analyst time. 3-day reports generated in hours.
Contrastive learning for alert correlation, LLM-powered incident reasoning with RAG over runbooks, agentic auto-remediation — and avoiding the false-positive trap.
How we combine LoRA fine-tuning, RAG retrieval, and zero-trust deployment to ship domain LLMs at a fraction of the cost of closed APIs.
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