AI solutions built
for real business needs.

From internal document assistants and customer-service chatbots to business automation, Machine Learning, Deep Learning and recommendation systems.

JDAMSK

Pragmatic solutions
built around your business goals.

AICORE
LLMIntelligence
DATAKnowledge
APIProduct
Cloud
PERFORMANCE+42%
agent.run(task)

TECHNOLOGIES

PythonPyTorchTensorFlowScikit-learnPandasNumPyHugging FaceOpenAIAnthropicLangChainLangGraphFastAPIMLflowDockerAWSAzureGCPPostgreSQLQdrant
01: SERVICES

What I can do
for your business.

Start from your problem, not from a technology. I can build the solution, improve an existing project, or help you decide where AI is genuinely useful.

02

Machine Learning & Deep Learning

I design complete ML and DL projects, from data preparation and modeling to evaluation and deployment.

  • Classification, regression, scoring and risk prediction
  • Forecasting, time series and anomaly detection
  • Clustering, customer segmentation and behavioral analysis
  • Recommendation and ranking systems
  • NLP: text classification, extraction and semantic analysis
  • Computer vision: image classification, detection and inspection
For you if: you want to predict an outcome, automate a decision, understand complex data, images or text, or personalize an experience.Discuss your ML project
03

AI Consulting & Automation

I help you determine where AI can create value, choose the right priorities and turn them into an achievable plan.

  • Business-needs discovery and process analysis
  • Identification and prioritization of AI use cases
  • Value, feasibility, data-readiness and risk assessment
  • AI roadmap, target architecture and technology choices
  • Review of existing projects, models and workflows
  • LLM benchmarking, cost analysis and cloud/on-premise choices
  • Document, email and business-process automation
For you if: you need a clear starting point, an independent technical opinion, or a plan to move from an idea to implementation.Explain your current situation
04

1-to-1 AI Coaching

I help you learn AI, Machine Learning and Deep Learning through a personalized roadmap and practical work.

  • Clear explanations adapted to your level
  • Guided exercises and personal projects
  • Code reviews and progress tracking
For you if: you want individual support instead of a generic course.See how coaching works
START SMALL

Focused ways
to begin.

Not every collaboration needs to start with a full build. A short engagement can clarify value and reduce risk.

01

AI Discovery Workshop

Prioritize use cases, assess data readiness and define a realistic roadmap.

1–2 workshops
02

RAG or Architecture Audit

Review retrieval, prompts, evaluation, costs, security and production risks.

Prioritized action plan
03

LLM Benchmark

Compare models across quality, latency, privacy and cost.

Cloud · Open source · On-premise
04

Feasibility Prototype

Test the riskiest assumption before investing in a complete product.

Focused proof of value
PRODUCTION AI

Beyond the demo.
Built to be trusted.

Reliability, security and operating cost are treated as engineering requirements from the start.

Request a system review ↗
01

Evaluation & groundedness

Test datasets, retrieval quality and checks against unsupported answers.

02

Guardrails & human control

Validation rules, confidence thresholds and human review where judgement matters.

03

Monitoring & observability

Trace failures, latency, token usage and cost after launch.

04

Security & maintainability

Access boundaries, data protection, documentation and clean handover.

03: SIMILAR CLIENT PROJECTS

Examples of projects
delivered for other clients.

View detailed similar projects
02CUSTOMER SERVICE · AGENTS

Multi-Agent Customer Service Chatbot

Built a modular conversational architecture where specialized agents collaborate to understand requests and deliver the right response.

  • FAQ, support and routing agents
  • Conversational memory management
  • Decision logic and agent orchestration
Multi-agentLLMMemory
03E-COMMERCE · DATA SCIENCE

Segmentation & Hybrid Recommendations

Developed a product data solution to better understand customer groups and generate more relevant product recommendations.

  • K-means customer segmentation
  • Content-based recommendation engine
  • Cosine similarity applied to embeddings
K-meansEmbeddingsPython
04CONSTRUCTION · NLP

Business Data & Recommendation Corpus

Structured fragmented industry data with NLP and prepared a reliable corpus for a future recommendation chatbot.

  • Data normalization and corpus preparation
  • Intent taxonomy and matching logic design
  • Foundations for conversational recommendations
NLPDataChatbot
05STRATEGY · BENCHMARKING

GenAI Use Cases & LLM Benchmark

Assessed high-value generative AI opportunities and compared open-source and proprietary models across deployment scenarios.

  • Business use-case prioritization
  • Quality, cost, latency and privacy comparison
  • Cloud and on-premise deployment assessment
GenAILLM EvaluationCloud
06ARCHITECTURE · AUTOMATION

Business-Aligned AI Workflows

Designed practical AI workflows that connect business requirements with existing applications, data sources and IT constraints.

  • Process analysis and automation mapping
  • Integration points and architecture definition
  • Security, maintainability and scalability planning
WorkflowsArchitectureAPIs
07KNOWLEDGE · ENTERPRISE AI

Enterprise Knowledge Assistant

Developed an LLM and RAG assistant that helps teams leverage internal documentation through natural-language questions.

  • Knowledge-base ingestion and retrieval
  • Context construction and answer generation
  • Focus on useful, traceable business answers
RAGLLMKnowledge Base
08TRAINING · AI LITERACY

Introduction to Artificial Intelligence

Delivered accessible introductory sessions to help non-specialists understand AI capabilities, limitations and business applications.

  • Core AI and generative AI concepts
  • Practical examples and responsible usage
  • Interactive discussion tailored to the audience
TrainingGenAIBusiness
04: MY PROCESS

Clear. Fast.
Production-ready.

No prototypes left gathering dust in a notebook. Every project is designed to be used, maintained and grow with your business.

✓ Business-oriented✓ Clean architecture✓ Clear communication✓ Fast delivery
  1. 01

    Discovery

    Goals, constraints, data and success metrics.

  2. 02

    Architecture

    Technology choices, security and delivery plan.

  3. 03

    Development

    Short cycles, demos and continuous validation.

  4. 04

    Deployment & support

    Production launch, monitoring and continuous improvement.

05: FAQ

Frequently asked
questions.

Another question? Get in touch.

How long does it take to launch an AI project?+

A useful first product typically takes 2 to 8 weeks, depending on integrations, available data and security requirements.

Can you work with our technical team?+

Yes. I can work independently or join your team to provide expertise, architecture and acceleration.

How do you protect data confidentiality?+

Security is built in from day one: access control, encryption, data isolation, logging and providers aligned with your requirements.

We do not know where to start. Can you help?+

Yes. A discovery workshop identifies the highest-impact use cases and creates a realistic roadmap.

HAVE A PROJECT IN MIND?

Let’s build AI
that truly matters.

Tell me about your project, current situation and expected outcome.

Start the conversation Project and coaching requests