Arash Nicoomanesh
Agentic AI Architect
Deterministic Core · Stochastic Range · Multi-Agent Scale
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
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...
CBT Autonomous Agent
Scalable, evidence-guided workflows that detect cognitive distortions and adapt to responses.
View Case Study → Research tool — not a clinician replacement.Emotion-Focused Agent
Supports deep emotional processing through sentiment trends and schema mapping.
View Case Study →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 →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
Is RAG Dead in 2025?
Rethinking documentation Q&A with large-context LLMs
Talk: Agentic RAG in Healthcare
15-min deck on self-evolving retrieval agents
Consulting Services
Build and Operate Intelligent Systems that Last
The Blueprint
AI Strategy & Advisory
The Forge
Solution Development
The Nexus
Deployment & Scale
Training & Knowledge Transfer
Mentoring & Education
Rapid POC Accelerator
Fast Validation
Specialized Agentic AI Solutions
Agentic AI Systems
