You will get an AI agent architecture plus a working prototype for your use case
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Project details
"Agent" covers everything from a single tool call to a system that plans, retries and coordinates other agents. Most projects go wrong by starting to build before deciding which one they need.
This sprint settles the design and proves it on your real use case.
What I do:
• Define the task boundary — what the agent decides versus what stays deterministic code
• Design the tool layer: what it can call, with what permissions, and what it must never touch
• Choose the pattern — single agent with tools, planner/executor, or multi-agent
• Handle state and memory so long tasks don't lose context
• Build guardrails: step limits, cost caps, validation, human approval where it matters
• Model cost per task at your expected volume — this kills more agent projects than accuracy does
• Build a working prototype against one real workflow of yours
Stack: Python · LangGraph · function calling · Celery/Redis · OpenAI or Claude
What you get:
An architecture document, a running prototype, a cost model, and a roadmap to production with effort estimates.
Good fit if: you have a multi-step process you'd like automated and need to know whether an agent can genuinely do it before funding the build.
This sprint settles the design and proves it on your real use case.
What I do:
• Define the task boundary — what the agent decides versus what stays deterministic code
• Design the tool layer: what it can call, with what permissions, and what it must never touch
• Choose the pattern — single agent with tools, planner/executor, or multi-agent
• Handle state and memory so long tasks don't lose context
• Build guardrails: step limits, cost caps, validation, human approval where it matters
• Model cost per task at your expected volume — this kills more agent projects than accuracy does
• Build a working prototype against one real workflow of yours
Stack: Python · LangGraph · function calling · Celery/Redis · OpenAI or Claude
What you get:
An architecture document, a running prototype, a cost model, and a roadmap to production with effort estimates.
Good fit if: you have a multi-step process you'd like automated and need to know whether an agent can genuinely do it before funding the build.
AI Algorithms
Autoencoder, Deep Belief Network, Generative Adversarial Network, Long Short-Term Memory Network, Radial Basis Function Network, Restricted Boltzmann Machine, Self-Organizing Map, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Music, Speech Synthesis, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, Copy.ai, GitHub Copilot, Jasper AI, Microsoft CNTK, NVIDIA AI Platform, Replit, Streamlit, Word2vecAI Models
AlphaCode, ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-J, GPT-Neo, LaMDA, Naive Bayes Classifier, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$1,600
|
Standard
$4,500
|
Advanced
$7,500
|
|---|---|---|---|
| Delivery Time | 7 days | 16 days | 24 days |
Number of Revisions | 1 | 2 | 2 |
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
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JO
Joerg O.
Apr 16, 2026
Full Stack Development
I highly recommend working with Stan - he ramped up on our complex multi-agent AI architecture remarkably fast, understood the full project structure within days, and played a key role in delivering on our launch deadline. Reliable, sharp, and a clear communicator.
DH
Daniel H.
Apr 10, 2026
Senior Python Developer to Build SMS-to-AI MVP SaaS (Django, React, Africa’s Talking, and OpenAI)
I worked with Stanislav on M-JIBU, an SMS-based AI assistant built for the Kenyan market. The platform allows users without internet access to interact with AI through basic text messages on any mobile phone, with payments handled via M-PESA and messaging routed through Africa's Talking API.
Stanislav was responsible for building out the entire backend infrastructure using Python, Django, Django REST Framework, PostgreSQL, Celery, Redis, all containerized with Docker and Docker Compose and deployed on a VPS. He also handled the integration work with Africa's Talking for SMS delivery and M-PESA for mobile payments, which are critical to the product's functionality.
Two things stood out about working with him. First, he moved through the development work very fast without cutting corners. Second, when we ran into unforeseen delays on our side related to licensing and administration, development had to be put on hold for a period. Stanislav was completely understanding about the situation and patient throughout. When we were ready to pick things back up, he jumped right back in.
I would not hesitate to work with Stanislav again and would recommend him to anyone looking for a dependable, skilled backend developer.
Stanislav was responsible for building out the entire backend infrastructure using Python, Django, Django REST Framework, PostgreSQL, Celery, Redis, all containerized with Docker and Docker Compose and deployed on a VPS. He also handled the integration work with Africa's Talking for SMS delivery and M-PESA for mobile payments, which are critical to the product's functionality.
Two things stood out about working with him. First, he moved through the development work very fast without cutting corners. Second, when we ran into unforeseen delays on our side related to licensing and administration, development had to be put on hold for a period. Stanislav was completely understanding about the situation and patient throughout. When we were ready to pick things back up, he jumped right back in.
I would not hesitate to work with Stanislav again and would recommend him to anyone looking for a dependable, skilled backend developer.
DD
Deyan D.
Feb 5, 2026
Experienced Python Django Developer (Part-time, Ongoing Project)
Stanislav was working with us on an internal gas trading web platform built with Python and Django, deployed on AWS. He demonstrated a strong understanding of Django, Django Admin, and backend architecture, and was able to quickly get up to speed with an existing production system. His Python skills are solid, communication was clear on both technical and business topics, and tasks were delivered reliably. Overall, a professional and dependable developer, and a good experience working together.
ST
Sam T.
Feb 4, 2026
Senior Python Developer for Quoting App Automation with Django, React, and Docker
Stanislav finished MVP automation tool for us. He worked fast and with high quality. I appreciated his thoughtful planning approach. He shared his architectural approach and asked for feedback on that early on, which helped move the project along smoothly. His communication skills were great (spoken, written, demeanor). Super easy to work with.
JN
Julian N.
Jan 6, 2026
Senior Python Developer for Web-Based Quotation for HVAC
Very professional and happy to work with Stanislav again!
About Stanislav
Senior Python Developer | AI App RAG | SaaS Web MVP
100%
Job Success
Vinnytsia, Ukraine - 8:30 pm local time
Need AI that works in production rather than a demo? That's my core strength — agents that carry out multi-step work, RAG over your own data, and the Django/FastAPI backends that make them reliable. Recent builds include an AI telephonic agent platform on Python/Azure and an SMS-to-AI assistant serving users with no internet access.
I also own backend-heavy work end to end — database and API design, integrations, deployment — and help teams fix slow, messy, or hard-to-maintain Python/Django codebases by restructuring logic, stabilizing APIs, and cutting technical debt. I deliver end-to-end SaaS MVPs too: admin flows, auth, billing, deployment.
𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱:
🟢 AI & LLM features — agents, RAG, OpenAI, Claude, LangChain, LangGraph
🟢 Multi-agent systems and workflow automation (Celery, Redis)
🟢 SaaS backends and MVPs (Django / DRF, FastAPI)
🟢 REST APIs, webhooks, and third-party integrations
🟢 Admin panels, authentication, roles & permissions
🟢 Refactoring & scaling legacy Python / Django systems
🟢 Docker-based deployment, AWS, and CI/CD
𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗵𝗶𝗿𝗲 𝗺𝗲 𝘁𝗼:
🟢 Add AI / LLM functionality to an existing platform
🟢 Build an AI-first product — agents, assistants, RAG over their own data
🟢 Launch the backend for a new SaaS product
🟢 Stabilize and scale an existing Django application
🟢 Build APIs and integrations that scale reliably
🟢 Automate manual business workflows
🟢 Get senior-level execution without unnecessary complexity
𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲:
Over 10+ years I've shipped products across SaaS, fintech, healthcare, education, and internal business tools. I build modular, well-structured systems that stay easy to extend as your product grows — especially strong in API-heavy platforms, async workflows, and third-party integrations.
𝗖𝗼𝗿𝗲 𝘀𝘁𝗮𝗰𝗸:
Python · Django · Django REST Framework (DRF) · FastAPI · PostgreSQL · MySQL · Celery · Redis · Docker · AWS · GitLab CI/CD · REST APIs · Webhooks · Stripe · Twilio · OpenAI · Claude · LangChain · LangGraph · React
𝗛𝗼𝘄 𝘄𝗲 𝘀𝘁𝗮𝗿𝘁:
For projects where the scope needs validation, I offer a paid discovery phase — a practical way to align on architecture, priorities, and a delivery plan before a larger engagement. You leave with a clear roadmap, fixed next steps, and no guesswork.
If you need a solid Python/Django backend, clean REST APIs, AI integrations, and senior-level execution with clear communication, send me a message — I'll reply with honest feedback on your project.
Steps for completing your project
After purchasing the project, send requirements so Stanislav can start the project.
Delivery time starts when Stanislav receives requirements from you.
Stanislav works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff — map the workflow, agree the task boundary
Design agent architecture, tools and guardrails