Precision-Engineered AI Architectures
Three solution pillars bridging deterministic control theory with production-grade agentic systems — each backed by measured ROI case studies.
Multi-agent orchestration with mathematical guardrails
Design and deploy self-correcting LangGraph workflows, deterministic tool-calling pipelines, and supervisor-governed state machines that maintain enterprise auditability while scaling agentic reasoning.
- Multi-agent LangGraph workflows with supervisor consensus
- Self-correcting finite-state machines with rollback semantics
- Deterministic tool calling with schema-validated I/O
Fault-tolerant control at the edge
Bridge microcontroller neural inference, switched dynamical systems, and MQTT telemetry pipelines into mission-critical automation architectures with Lyapunov-stable control guarantees.
- Microcontroller neural inference (TensorFlow Lite, ONNX Runtime)
- Fault-tolerant PID/MPC control loops with observer design
- Switched dynamical systems and hybrid automata modeling
Fractional AI leadership with engineering rigor
Fractional AI CTO engagements, technical feasibility audits, and enterprise roadmaps grounded in control-theoretic risk modeling — not slide-deck AI strategy.
- Fractional AI CTO and architecture board participation
- Technical feasibility audits with TCO/ROI modeling
- Enterprise AI roadmaps with phased delivery milestones