Production systems built on our context-engineering principles. Each MVP demonstrates end-to-end AI integration — from autonomous operation to self-healing infrastructure.
Real-time endpoint security monitoring for macOS
Obsidian Halo is a privacy-first cyber defense platform that runs entirely on-device. It delivers enterprise-grade threat detection, nation-state attribution, and real-time threat intelligence — all processed locally on Apple Silicon with zero cloud dependencies.
On-device AI analysis powered by Llama 3.2 running locally via MLX provides intelligent threat assessment without sending data to external AI providers. Obsidian Halo also integrates with Anthropic Claude AI Opus 4.6 — functioning as an AI-powered cyber security threat analyst, cyber threat incident responder, and cyber forensic investigator. Install once, protection forever.
All analysis runs on-device. Security data never leaves your Mac — no cloud, no subscriptions, no data harvesting.
Built from the ground up for M1/M2/M3/M4 chips with neural engine acceleration.
146 detection rules covering 75 MITRE ATT&CK techniques. Same methodology used by Fortune 500 SOCs.
Matches attack patterns against 10 APT groups (Russia, China, North Korea, Iran) with YARA-based signatures.
18+ threat feeds with automatic 6-hour refresh. Spamhaus, FireHOL, Tor exit nodes, and Feodo tracker integration.
Llama 3.2 LLM runs locally via MLX for on-device threat assessment with zero data exfiltration.
Anthropic Claude serves as cyber threat analyst, incident responder, and forensic investigator — advanced reasoning for complex threat analysis.
DuckDuckGo Tracker Radar integration identifies fingerprinting and cross-site tracking in real-time.
Install once, protection forever. No agents to configure, no policies to manage, no cloud console.
AI-enhanced OSINT analytics — autonomous intelligence aggregation, analysis, and delivery
The AlphaOne Daily Intelligence Briefing is an AI-enhanced OSINT (Open Source Intelligence) analytics platform — a fully autonomous, end-to-end AI pipeline that collects, validates, scores, analyzes, and delivers curated intelligence briefings with zero human intervention. It provides AI-driven analysis of the current global risk picture across geopolitical, cyber, economic, and technology domains.
Available on iOS, Android, and desktop web, the briefing is delivered as a native mobile experience with responsive dashboards optimized for each platform. The system operates on a self-healing architecture where AI agents continuously monitor their own health, detect anomalies, and autonomously remediate failures across the entire pipeline.
Every stage of the pipeline is AI-driven. No manual curation, no human gatekeepers, no scheduled batch jobs waiting for someone to press a button.
AI-managed feed watchdog continuously monitors and ingests intelligence sources. Adaptive scheduling adjusts collection frequency based on source reliability and freshness signals. Failed feeds are automatically retried with exponential backoff.
Every ingested item passes through AI-powered schema validation and quality scoring. Structured schemas enforce data integrity while quality scorers assess relevance, credibility, and timeliness — filtering noise before it enters the pipeline.
All validated intelligence is stored in a graph database that maps relationships between entities, sources, topics, and temporal patterns. Graph traversal enables multi-hop reasoning that flat databases cannot support — connecting dots across disparate intelligence domains.
LLM-powered analysis synthesizes collected intelligence into structured briefings. Context-engineered prompts ensure consistent output quality. The generator produces responsive dashboards for both desktop and mobile with real-time data visualization.
Finished briefings deploy automatically to desktop and mobile platforms via Cloudflare Pages. Deployment pipelines validate output integrity before going live. Zero-downtime delivery ensures consumers always have access to the latest intelligence.
A dedicated AI health monitoring system continuously observes every component in the pipeline. It detects feed failures, data quality degradation, pipeline stalls, rendering errors, and infrastructure anomalies — then autonomously remediates without human intervention.
The health monitoring system operates as an independent AI agent that treats the briefing pipeline as its observability domain.
Health agents poll every pipeline stage — feed latency, schema validation pass rates, graph DB query performance, generation success rates, and deployment status. Metrics are collected into a dedicated health dashboard with real-time visualization.
AI-driven anomaly detection identifies deviations from baseline behavior. Feed staleness, quality score drops, generation failures, and deployment errors trigger graduated alert levels — from advisory through critical.
When anomalies are detected, the health system autonomously executes remediation workflows: restarting failed feeds, re-triggering generation passes, rolling back bad deployments, and escalating only when automated recovery is exhausted.
A dedicated health monitoring dashboard provides real-time visibility into pipeline status, component health scores, remediation history, and system-wide metrics — giving operators confidence the system is operating within spec.
These MVPs demonstrate what's possible when AI is engineered into every layer of the stack. Let's talk about your use case.
sales@alpha-one.mobi