monigarr - Overview
For agencies and partners deploying AI in high-consequence environments: my work provides the verification layer between generative output and institutional trust.
⚡ MoniGarr
AI-First Systems Architect | Federal Compliance & Autonomous Navigation Gauntlet for America Cohort 2 | Low-Resource Language Formalization
Focused Mandate
I architect deterministic, auditable, and ethically-bounded AI systems for high-risk institutional deployment. My practice bridges the gap between generative AI capability and federal-grade reliability—specifically in degraded environments (GPS-denied, low-bandwidth, adversarial input).
Core Competencies (Enterprise & Federal-Facing)
| Domain | Implementation Focus | Relevant Repo |
|---|---|---|
| Autonomous Navigation | Belief state tracking, GPS-denied pathfinding, failure mode refusal | SMBNA |
| Edge AI / Android | Real-time vision streaming, DRM, QoS for defense logistics | fluvian-sdk |
| Low-Resource LLMs | Custom tokenization (polysynthetic), QLoRA fine-tuning, sovereignty | mini-indig-llm-kit |
| Deterministic RL | Modernized SAC agents, Gymnasium/MuJoCo, evaluation pipelines | spinningup (fork) |
| Agentic Safety | Formal verification of LLM tool-use, institutional constraint layers | ai-ethos-registry |
| XR Training Environments | Procedural generation for high-consequence simulation | `` |
Technical Arsenal (Hardened Stack)
Inference/Backend: PyTorch, TensorFlow, JAX, vLLM, Triton Infrastructure: AWS (GovCloud ready), Vercel, Railway, Docker, K8s Agent Frameworks: LangChain, LangGraph, AutoGen, DSPy RL/Control: Gymnasium, MuJoCo, RLlib, Stable-Baselines3 Vision/Edge: OpenGL, Vulkan, Android NDK, MediaCodec Governance: MLflow, LangFuse, LangChain, Pydantic, Great Expectations
Engagement
Open to AI-first architecture, AI engineering, applied research, federal technology, healthcare AI, responsible AI infrastructure, and mission-critical system design roles.
LinkedIn: https://www.linkedin.com/in/monigarr
Contact: monica.peters@gfachallenger.gauntletai.com