Proof, Not Promises
Production AI systems we've built. Real metrics, named technologies, engineering decisions explained. Start with the evidence closest to your current decision, not the newest item in the archive.
Validate & Govern High-Stakes Systems
Proof for enterprise review, governance architecture, and systems where the question is not only whether the model works, but whether the decisions can be trusted and explained.
Axion Engine: Adversarial R&D Operating System
Domain-agnostic R&D pipeline where three models attack each other's output across CS, clinical medicine, and IoT firmware.
Enterprise Data Governance & Document Classification Platform
We engineered a smart document classification and anomaly detection system for an enterprise client, enabling automated GDPR compliance through ML-driven categorization of corporate files across multiple languages.
Real-time anomaly detection processing 2.4M events/day with 70% fewer false positives
How we built a real-time anomaly detection pipeline processing 2.4M events/day using Kafka, Isolation Forest, and foundation models. False positive rate reduced from 68% to under 20%.
Build Agent Systems For Live Use
Proof for teams shipping agents, HITL workflows, RAG systems, and operational automation into environments with real users and real failure cost.
Autonomous PPC Engine with 72-Hour Signal Lead Time
Real-time signal intelligence from GitHub Issues and StackOverflow, dual-angle creative, and edge-deployed landing pages at 15ms TTFB.
Competitor Intelligence Agent: 8 Hours to 5 Minutes
Multi-agent system with parallel execution. Automated competitive analysis across pricing, features, and positioning with structured Pydantic-validated output.
Codebase Analysis Agent: 30 Seconds to First Answer
Language-aware chunking with Tree-sitter, FAISS vector retrieval, and LLM reasoning. 30 seconds from upload to first contextual answer on any codebase.
Aporia: Modular OSINT Engine for Security Research
We built an autonomous OSINT (Open Source Intelligence) engine that gathers publicly available information about targets and produces structured intelligence reports through a modular agent-based architecture.
Autonomous Content Engine with Multi-Model LLM Pipeline
Multi-model LLM pipeline with 12 Pydantic validators, auto-generated D2 diagrams, and HITL review — replacing $600 freelance articles.
Scale Data & AI Platforms
Proof for buyers evaluating real-time data infrastructure, computer vision systems, and production AI platforms with downstream operating dependencies.
Real-Time IoT Analytics Platform for Smart Agriculture
We built a real-time streaming analytics platform for an AgriTech startup, processing live GPS data from farming equipment to track field coverage, calculate equipment utilization, and deliver dynamic ETAs to mobile devices.
High-Throughput Real-Time Facial Recognition Platform
Distributed facial recognition system processing millions of concurrent video streams with >97% accuracy using FaceNet embeddings, Kafka streaming, and k-NN matching.
AI-Powered Video Interviewing & Candidate Analysis Platform
We built an end-to-end video interviewing platform with real-time speech-to-text transcription, automated resume parsing, and semantic search — enabling recruiters to find key candidate responses in seconds.
Telos: Deterministic AI Video Infrastructure
Cinema-grade AI video engine with strict temporal logic, locked character persistence, and fully deterministic latent space navigation. Every frame is intentional.
Let's architect your next system
Submit system context, constraints, and delivery pressure. A Principal Engineer reviews every submission and recommends the right next step.
1. Context
We review the system, constraints, and where risk is most likely to surface.
2. Recommendation
You get a direct recommendation: audit, advisory, sprint, or pause.
3. Next Step
If there is a fit, we define the shortest useful engagement.
No SDRs. A Principal Engineer reviews every submission.
From the team behind Production-Ready AI Agents (Amazon, 2025)