You will get a working AI agent or automation built for your task in 2 days
Rising Talent
Project details
You describe the task — an agent that runs a workflow, a script that ends a manual process, a bot that pulls and cleans data. I build it, run it on your input, and send a short recording of it actually working before you pay. No black box: every step and the exact action it takes is visible.
Built with Python, LangGraph, n8n, and the Claude or OpenAI APIs. Everything happens in writing — no calls. You get the code, a short setup guide, and revisions until it does exactly what you described.
Good fit for: lead follow-up, data entry and enrichment, document processing, report generation, scraping, internal tools, and connecting apps that don't talk to each other.
Tell me the task and what a good result looks like, and I'll say straight whether it's a fit and how I'd build it.
Built with Python, LangGraph, n8n, and the Claude or OpenAI APIs. Everything happens in writing — no calls. You get the code, a short setup guide, and revisions until it does exactly what you described.
Good fit for: lead follow-up, data entry and enrichment, document processing, report generation, scraping, internal tools, and connecting apps that don't talk to each other.
Tell me the task and what a good result looks like, and I'll say straight whether it's a fit and how I'd build it.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$120
|
Standard
$280
|
Advanced
$550
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 2 | 3 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | |
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | ||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
Frequently asked questions
About Bogdan
Senior Claude Code & MCP Engineer | Clinical AI, RAG, Multi-Agent
Kyiv, Ukraine - 12:20 am local time
13 years as a clinical psychologist before AI engineering — rare combination. I build agent systems that pass both engineering review and clinical scrutiny, because I've sat on both sides.
— What I build —
• MCP servers exposing internal tools to Claude Desktop / Claude Code — auth, rate-limiting, error paths, prompt-injection guards. Not generic forks; tuned to each client's workflow.
• Multi-agent systems: dispatcher → 3-7 specialized subagents → quality-gate layer → handoff protocol before context-compaction. Persistent memory, not prompt-stuffing.
• Hook + sandboxing layers: pre-action guards, post-action telemetry, watchdog daemons. The boring guarantees that make AI systems reliable instead of theatrical.
• Healthcare / clinical AI: PHI deidentification with crypto envelope chains, supervisor-grade audit logs, clinical formulation modules grounded in CBT/Schema/MAPS-track frameworks. Where most AI engineers don't have clinical context to know what to refuse.
— Recent work (anonymized where NDA) —
• EU clinical SaaS extension: 3-role architecture (patient / therapist / supervisor), 11,309 production lines across 8 files, full code-review 10+ rounds.
• B2B research pipeline: 430 manually verified contacts across 12 markets in 2 weeks. Custom triangulation + Airtable delivery. over 2x cold-database response rate.
• Open Claude Code reference implementation: 20+ specialized agents, MCP integrations, memory layer, hook system, bridge architecture. Production-grade, used as my own daily ops for 12+ months.
— Stack —
Anthropic Claude (Fable 5 / Opus 4.8 / Sonnet 4.6 / Haiku 4.5), MCP (stdio + HTTP), LangGraph, RAG (ChromaDB / vector DBs), Python, TypeScript, Node.js, n8n.
— How I work —
First engagement = fixed-price milestone: scope doc (day 1-2), working system (day 5-10), production handoff (day 12-14). One revision. Daily git pushes — you audit progress async.
Bilingual EN/UA/RU.
— CTA —
Send your use case (workflow + pain point + stack). I reply within 24h on weekdays with yes/no + rough scope, or a referral if not my fit.
Steps for completing your project
After purchasing the project, send requirements so Bogdan can start the project.
Delivery time starts when Bogdan receives requirements from you.
Bogdan works on your project following the steps below.
Revisions may occur after the delivery date.
You share the task and a sample
You describe what the agent or automation should do and send a sample of your input, plus any tools it must connect to.
I build it and run it on your data
I build the agent or automation and run it on your input, then send a short recording of it working end to end.