Medical Triage Agent
Hybrid conversational agent using Gemini Pro, Med-PaLM 2
Engineered to mimic a clinician's stepwise reasoning process, combining multiple AI technologies for comprehensive patient assessment and support
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"
- The era of "chat" is over. Businesses need systems that read reports, flag risks, draft notices, and update ledgers — while they sleep. Intelligence without execution is just entertainment.
- Most "AI Agents" fail the Planning Rubicon — they react but never truly plan, execute, or persist state across time. Stateless LLM wrappers are expensive chatbots, not autonomous systems.
- True agentic architectures separate the "brain" (stochastic reasoning) from the "skeleton" (deterministic execution). Governance first, intelligence second — because intelligence without control is liability.
Selected Case Studies
Conversational Drug Repurposing
Applying Google LLMs for alternative therapy recommendations from RWD EHR
The generator uses advanced AI techniques to analyze biomedical data and generate novel hypotheses for drug repurposing
ICU Metrics Forecasting
Multi-variate time-series models predicting readmission, mortality and LOS using clinical variables
Multi-Turn Product Recommendation QA Bot
Fine-tuned open source LLMs with hybrid retrieval with efficient inference and scalable deployment
Banking Resource Management System
End-to-end customer LTV and churn prediction as well as transactional fraud detection
Covid-19 Diagnosis with Audio Biomarkers
COVID-19 diagnosis through acoustic analysis of breathing, cough, and speech signals
Featured Articles
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 reasoning prompts and guardrails for reliable outputs
Few-Shot & Zero-Shot Learning Deep-Dive
Push LLMs beyond narrow fine-tuning.
In the age of large language models (LLMs), the ability to perform complex tasks with minimal data is revolutionizing how we approach artificial intelligence. Few-shot and zero-shot learning are two pivotal techniques that push the boundaries of machine learning, enabling models to generalize across domains and perform tasks they were not explicitly trained on. This article delves into these learning paradigms, explaining their origins, mechanisms, and real-world applications
Model Drift: A Survival Guide
Monitor & remediate production ML models
Fine-Tune Gemma-3 12B with Unsloth
End-to-end Unsloth & TRL workflow for customer service
In this article, I have dived into the technical intricacies of Unsloth and Gemma 3, showcasing their powerful features and how they can be leveraged together to build a highly optimized, fine-tuned model for any type of customer support assistant, whether it be a sophisticated chatbot, an intelligent agent, or an interactive FAQ system. I provided a step-by-step guide through the fine-tuning process, from data preparation to model deployment, highlighting best practices and practical considerations for achieving optimal performance in real-world customer service scenarios
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
Ways I Help
AI Strategy & Advisory
< The Blueprint >
Identify high-ROI AI opportunities and receive a detailed technical roadmap to build a powerful, custom AI solution.
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Solution Development
< The Forge >
Take the architectural plan, forge your strategic blueprint and bring it to life through rigorous engineering, testing, and iteration.
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Deployment & Scale
< The Nexus >
Production deployment, LLMOps, monitoring, cost optimizations and team handover. Phased contracting available.
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Training & Knowledge Transfer
Mentoring tailored to your goals— ML engineers or data scientists who want to level-up fast or LLM Engineers who want to build a custom curriculum.
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Rapid POC Accelerator
Fast, focused build to validate product/technical fit. We deliver an interactive demo, integration smoke-tests, and a clear go/no-go recommendation.
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Specialized Agentic AI Solutions
Design and ship multi-step agents that reason, call tools, and integrate with systems (APIs). Focused on observability, guardrails, so agents can operate reliably in production.
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