Agentic AI

AI that plans, uses tools, and stays under control.

I help teams ship practical AI — from model-backed features to agent workflows that retrieve context, call tools, and ask before they do something risky.

AI Systems

Useful in production — not just impressive in a demo.

Models, retrieval, tool calling, and guardrails working together. The goal is reliable action, not unbounded autonomy.

ML / DL when prediction fitsGen AI RAG & LLMsAgents plan, act, check
Talk about an AI workflow
Agentic AI architecture showing machine learning, deep learning, generative AI, and autonomous agents

From Models to Agents

Agentic AI builds on a full AI stack: machine learning for prediction, deep learning for complex patterns, generative AI for content and reasoning, and AI agents that orchestrate tools, memory, and workflows toward a goal—with guardrails and observability.

How I Help

  • ML/DL model design, training, and evaluation
  • Gen AI apps with RAG, fine-tuning, and APIs
  • AI agent architecture with tools and memory
  • Secure MLOps, monitoring, and production ops

AI Stack

A clear path from data to autonomous action

DataPipelines & features
ML / DLTrain & predict
Gen AILLMs & generation
AI AgentPlan & act
GovernEval & control

Machine Learning

Predictive systems grounded in data.

Supervised Learning

Classification, regression, ranking, and forecasting models

Unsupervised Learning

Clustering, anomaly detection, and dimensionality reduction

Reinforcement Learning

Policy learning for sequential decisions and optimization loops

Feature Engineering

Feature stores, transforms, and training-serving consistency

Model Evaluation

Metrics, validation strategy, bias checks, and A/B testing

Classical ML Stack

Scikit-learn, XGBoost, LightGBM, and production scoring services

Deep Learning

Neural networks for complex signals and media.

Neural Architectures

CNNs, RNNs/Transformers, embeddings, and custom deep models for structured and unstructured data.

Computer Vision

Image classification, object detection, OCR, and visual quality or moderation pipelines.

NLP & Speech

Text classification, NER, summarization, speech-to-text, and semantic search foundations.

Training at Scale

GPU workflows, distributed training, experiment tracking, and reproducible model runs.

Frameworks

PyTorch, TensorFlow/Keras, Hugging Face, ONNX, and efficient inference runtimes.

Model Serving

Low-latency APIs, batch scoring, model registries, and canary/rollback releases.

Generative AI

LLMs and generative systems that create, reason, and assist.

Gen AI Capabilities

  • Large language models (LLMs)
  • Prompt engineering & system design
  • RAG over private knowledge bases
  • Fine-tuning & adapters (LoRA)
  • Multimodal generation (text, image, code)
  • Structured output & function calling

Production Gen AI

  • OpenAI, Anthropic, Gemini, open-source LLMs
  • Vector databases & embeddings
  • Caching, rate limits, and cost controls
  • Hallucination reduction patterns
  • Content moderation & safety filters
  • Eval harnesses for quality and regression

AI Agents

Systems that plan, use tools, and complete work.

Agent Architecture

Planner-executor loops, memory, state, and goal-oriented workflows

Tool Use

APIs, browsers, databases, code runners, and enterprise system connectors

Multi-Agent Systems

Specialist agents that collaborate, hand off tasks, and review outcomes

Conversational Agents

Support, ops, and internal assistants grounded in company knowledge

Workflow Automation

Agentic pipelines for research, triage, reporting, and ops runbooks

Guardrails

Permissions, human-in-the-loop, audit logs, and policy enforcement

Agent Frameworks

LangChain, LlamaIndex, custom orchestration, and enterprise agent runtimes tailored to your stack.

Memory & Context

Short-term session memory, long-term stores, retrieval strategies, and context window management.

Reliability Patterns

Retries, fallbacks, deterministic tools for critical steps, and clear failure handling.

Observability

Tracing prompts, tool calls, latency, cost, and outcome quality in production.

MLOps & Governance

Ship AI safely and keep it measurable.

MLOps Pipelines

Training, validation, packaging, and deployment automation

Monitoring

Drift detection, performance tracking, and incident response for models

Responsible AI

Privacy, access control, red-teaming, and usage policies

AI Infrastructure

GPU/CPU serving, vector infra, queues, and secure backend integration

Evaluation

Offline evals, online experiments, and continuous quality gates

Business Integration

Connect AI agents to CRM, support, DevOps, ads, and internal systems

Agentic AI Partner

Move from AI demos to production systems your team can trust.

Whether you need a predictive ML model, a Gen AI knowledge assistant, or an agent that executes real workflows, you get architecture, implementation, and operational clarity.

Start Your AI Roadmap