Capabilities

Five pillars of applied AI — each grounded in real-world systems we’ve built and operate.

Expert Systems & RL Loops

Hypothesis-driven interview engines that reason over weighted knowledge graphs and improve autonomously through reinforcement learning feedback loops — no human labeling required.

  • Information-gain question selection with confidence-based termination
  • Weighted entity–signal knowledge graphs with context modifiers
  • RL self-learning loop: every completed case refines the model
  • Multi-layer NLP inference: KB matching, synonym expansion, textbook, vocabulary, fuzzy, negation
  • YAML-driven configuration for rapid domain generation

Robotics RL Pipelines

From-scratch reinforcement learning in JAX with a full deployment path to real-world robotics hardware via ONNX export and NVIDIA edge compute.

  • Pure JAX/Flax implementations: DQN, A2C, DDPG — every update step JIT-compiled
  • Multi-modal observation engine: pixel rendering, normalization, frame stacking
  • Gymnasium and MuJoCo environments for continuous control
  • ONNX export with parity validation for edge deployment
  • Target hardware: NVIDIA Jetson Orin / Thor via TensorRT or onnxruntime

Model Operations & Routing

Intelligent model evaluation, routing, and cost optimization — so every inference task uses the right model at the right price with full transparency.

  • Multi-provider routing with automatic quality/cost trade-off
  • Evaluation harnesses for accuracy, latency, and cost benchmarking
  • BYOK (bring your own key) architecture
  • Transparency reports showing per-task model selection rationale
  • Rust-native performance for production-grade throughput

Enterprise & Local-First Agents

Autonomous AI agents for enterprise workflows that run on your infrastructure — self-improving, context-aware, and fully under your control.

  • Integration with Teams, Outlook, Azure, and VS Code
  • Self-improving skill engine with autonomous discovery and refinement
  • Persistent vector memory with context-aware retrieval
  • Self-hosted architecture: no mandatory cloud dependency
  • RAG over business documents with provenance-tracked citations

Safety-Gated Clinical AI

Clinical decision support that shows its work, surfaces uncertainty, and keeps the clinician in command. Never diagnoses. Never prescribes. Always defers to qualified judgment.

  • Multi-specialty differential reasoning (cardiology, dermatology, pediatrics)
  • Under-triage treated as a hard failure in evaluation
  • Confidence thresholds and mandatory referral triggers
  • Evaluation-first development: ground-truth benchmarks before production code
  • Disclosure hard-stops and professional disclaimers at every interaction boundary

Need a capability we haven’t listed?

Our work spans healthcare, finance, education, and robotics. If you have a domain that needs intelligent systems, we should talk.

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