
ML-driven threat detection and continuous monitoring platform built for federal zero trust architectures.
ML-driven threat detection and continuous monitoring platform built for federal zero-trust architectures. OSCAL-native, FedRAMP Moderate-aligned, hash-chained audit, three-model anomaly ensemble.
make setup # install bun + python deps
make dev-up # bring up the local stack via docker compose
make dev # turbo dev across workspaces
make smoke # end-to-end smoke test
Open http://localhost:3000 for the dashboard.
| Path | Purpose |
|---|
docs/platform.md | Engineer onboarding entry point — start here |
docs/architecture.md | Master technical specification |
docs/deep-dive.md | Strategic positioning and market context |
docs/design.md | Visual design system |
docs/runbooks/ | Operations, DR, deployment, cost management |
compliance/ | OSCAL artifacts, threat models, KSI mappings, DFDs |
any, no untyped
functions.services/audit-sink/ for the hash-chained
audit log writer.apps/ # Next.js apps — marketing site and analyst dashboard
services/ # Backend services — api, alert-engine, audit-sink, ...
packages/ # Shared types and design tokens
infra/ # Docker, Helm, Terraform, OPA, demo deployment
compliance/ # OSCAL, threat models, FedRAMP KSI mappings, DFDs
eval/ # Datasets, performance harness, DR test, smoke tests
docs/ # Architecture, design, runbooks, deep dive
UNLICENSED — proprietary to Kreotic, Inc.