Arash Nicoomanesh
Agentic AI Architect
AI Engineering Services & Consulting
Don't Build Just "Expensive Chatbots" Real Agentic Systems Reason and Learn within Adaptive Architecture
Execution over Conversation
Build AI systems that read reports, flag risks, generate artifacts, and update systems autonomously while learning from outcomes. Intelligence that cannot act or improve from action is not a system; it's a demo.
Planning over Reaction
Most so-called "AI agents" respond to prompts but fail to plan, execute multi-step workflows, persist state, or refine behavior over time. Stateless LLM wrappers are costly — and fragile.
Control over Cleverness
Apply robust agentic architectures that separate stochastic reasoning from deterministic execution, enabling learning within explicit constraints. Governance, validation, and recovery come first.
Architecture Philosophy
Deterministic Core · Stochastic Range · Multi-Agent Scale
The Planning Rubicon
Why most "AI agents" are just expensive chatbots that react but never truly plan or execute.
From generative to agentic AI
The 2026 roadmap: why the future of AI isn't better brains, it's better bodies.
How LLM reasoning powers agency
How advanced LLMs enable true agentic behavior through reasoning and planning.
Agentic Solutions
Closed-loop autonomous systems with traceable reasoning and human-in-the-loop safety.
Medical Triage Agent
Reasons like a clinician; prioritizes care safely.
> [INIT] Agentic_Loop_v2.4
> [DATA] EHR Patient_ID: 99x-72 linked
> [THINK] Analyzing Vitals: BP 160/100, Temp 101F
> [REASON] Cross-ref: Type 2 Diabetes history
> [RISK] Sepsis Probability: 72% (Critical)
> [PLAN] Generating Priority_Alpha alert...
> Waiting for clinician auth...
Biomedical Hypotheses
Hypothesis-driven retrieval over PubMed/DrugBank for repurposing leads.
View Case Study →Marketing ROI Optimizer
Continuously reallocates budget using Multi-armed bandits and real-time conversion signals.
View Case Study →Supply Chain Orchestrator
Autonomously reroutes logistics based on inventory, weather, and telemetry.
View Case Study →Consulting Services
Build and Operate Intelligent Systems that Last
The Blueprint
AI Strategy & Advisory
De-risk your AI investment with a comprehensive technical architecture, cost model, and execution strategy
The Forge
Solution Development
Validate your AI idea in 4 weeks. We Build a production-grade prototype, not a throwaway demo
The Nexus
Deployment & Scale
Governance first, Intelligence second. Production architectures with Policy-as-Code, blast-radius containment, and durable execution.
Generative AI & LLM Engineering
Determinism, Neuro-Symbolic Logic and Optimization
Beyond APIs. Custom architecture, model optimization, and reliable engineering for high-stakes AI systems.
Moving beyond API wrappers, we re-engineer model architectures for production scale. We optimize neural weights for latency, implement custom precision tuning, and design dedicated inference layers that drastically reduce compute costs without sacrificing reasoning quality.
Specialized Agentic AI Solutions
Agentic AI Systems
Neuro-symbolic agents that do work. Separating the 'Brain' and reasoning from the 'Body' and execution. We implement hierarchical planning, self-correction loops, and "Blast Radius" protocols. Your agents won't just chat; they will safely execute complex workflows, verify their own outputs, and persist state across system failures.
Knowledge Base
Fine-Tuning DeepSeek R1 on Medical Chain-of-Thought
Latest technical walk-through on enhancing medical-reasoning LLMs with CoT fine-tuning
Gemma 3n Edge AI for Support Bots
Low-memory, high-speed training on customer-support data
LLM Output Config & Guardrails
Master temperature, top-p, and guardrails for reliable LLM outputs
Few-Shot & Zero-Shot Learning Deep-Dive
Push LLMs beyond narrow fine-tuning with cross-domain generalization
Fine-Tune Gemma-3 12B with Unsloth
End-to-end Unsloth & TRL workflow for customer service
Model Drift: A Survival Guide
Monitor & remediate production ML models before they fail
Talk: Agentic RAG in Healthcare
15-min deck on self-evolving retrieval agents
