How Our Neural Threat Engine Reduced False Positives by 94%
We rebuilt our threat detection pipeline from the ground up using a transformer-based architecture trained on 18 months of anonymized network telemetry. Here's a deep dive into the training data, model architecture, and real-world results.
Why We Chose WebAssembly for Our Edge Runtime
Exploring the tradeoffs between V8 isolates and Wasm modules at the network edge, and how we achieved deterministic cold-start times under 1ms.
Self-Healing BGP: How We Built a Network That Fixes Itself
A walkthrough of our autonomous routing recovery system that detects and reroutes around failures before humans even receive a PagerDuty alert.
The Hidden Cost of Multi-Cloud: What FinOps Won't Tell You
Data egress fees, cross-region latency, and operational complexity — the real price of multi-cloud strategies and how we help clients navigate them.
Zero Trust is Not a Product. It's a Philosophy.
Vendors are selling "zero trust" like it's a checkbox. We explain what it actually means architecturally and how to implement it without vendor lock-in.
Killing Alert Fatigue: Our ML Approach to Noise Reduction
How we trained a correlation model on three years of incident history to reduce alert volume by 87% while maintaining a 99.97% detection rate for real incidents.