AI agents and RAG systems
AI agents · RAG · LLM · Vector search · Qdrant
AI agents and RAG systems
I build AI tools that work with your documents, messages, files and structured data instead of relying only on a general-purpose model.
A useful production system combines retrieval, permissions, citations, tools, validation and a clear workflow around the model. It is more than a chat box connected to an API.
What can be automated
Knowledge search
Search and answer questions across policies, manuals, projects, correspondence and internal documentation.
Document processing
Classify, extract, compare and summarize documents while retaining links to the source material.
Employee assistants
Help staff find information, prepare drafts and perform approved actions in connected systems.
Data workflows
Combine LLM reasoning with deterministic APIs, databases, queues and validation rules.
How the system is built
The model is one component. Data quality, retrieval, permissions and evaluation determine whether the product is trustworthy.
Discovery
I clarify the users, business process, data sources, integrations, constraints and failure scenarios before choosing an implementation.
Requirements · workflows · risksArchitecture
I define the application structure, API boundaries, data model, permissions, queues and external integration points.
Backend · API · database · securityIncremental delivery
The work is split into testable stages so that the critical path can be reviewed before the entire system is complete.
Milestones · reviews · predictable scopeLaunch and support
I verify real workflows, logging, error handling and background jobs, then help maintain and extend the solution.
Monitoring · logs · support
Production safeguards
Grounding and citations
Answers use retrieved context and can expose the documents or fragments that support them.
Permission-aware retrieval
Users only retrieve information they are already allowed to access.
Evaluation and fallback
Representative tests, confidence checks and human review reduce silent failure.
Technology and delivery
Expected result
An AI system grounded in your data, integrated into a practical workflow and designed so that answers and automated actions can be checked and improved.
AI Agents · RAG · LLM · Qdrant · Vector Search · Knowledge Base · Automation
Discuss your project
If you have a project involving Python, Laravel, Node.js, CRM, Telegram, AI/RAG, API integrations, automation or TON/GRAM logic, send me a short description of what you need.
You can simply explain what exists now, what is not working, what outcome you expect and which services are already involved.