A commercial decision engine designed as a control system for agentic AI architectures. The Xybernetex API enforces structured state transitions, deterministic arbitration, and auditable reasoning over probabilistic language models.
Request Beta AccessThe Xybernetex API is not a prompt wrapper. It is a structured execution layer that integrates Markov Decision Processes, Monte Carlo Tree Search, and deterministic verdict logic to constrain and evaluate reasoning paths generated by large language models.
The model generates reasoning. The engine scores, filters, and decides.
Explicit thresholds override model self-evaluation. The LLM cannot hallucinate a passing result past defined decision criteria.
Multi-stage reasoning with defined transitions ensures coherence across problem framing, risk assessment, and final recommendation.
Every execution produces machine-readable audit artifacts suitable for enterprise review, compliance, or governance.
Designed for orchestration layers that require episodic decision checkpoints rather than continuous prompt chaining.
The hosted API will provide optimized execution speed, hardened reliability, versioned contracts, and enterprise-grade deployment options.
We are onboarding a limited number of technical partners building agentic systems who require deterministic control over stochastic model outputs.