You will get a Custom LLM on Your Data (RAG → Fine-Tune if ROI) in 7 Days


Project details
You will get a production-ready LLM on your data — shipped in 7 days with evals, cost guardrails, and full ownership.
No generic AI fluff. I build retrieval-augmented generation (RAG) pipelines that answer in your tone, cite sources, and reduce hallucinations. Fine-tuning is included only if it beats baseline and pays off.
You’ll receive eval reports (accuracy, latency, cost), a deployable app (API or UI), full source code, and clear documentation. I work inside your cloud/accounts — no lock-in, no hidden infra bills.
If you want an LLM that works, not just “talks smart,” I deliver.
No generic AI fluff. I build retrieval-augmented generation (RAG) pipelines that answer in your tone, cite sources, and reduce hallucinations. Fine-tuning is included only if it beats baseline and pays off.
You’ll receive eval reports (accuracy, latency, cost), a deployable app (API or UI), full source code, and clear documentation. I work inside your cloud/accounts — no lock-in, no hidden infra bills.
If you want an LLM that works, not just “talks smart,” I deliver.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Enhanced Classification, Conversational AI, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, NVIDIA AI Platform, PyTorch, StreamlitAI Models
BERT, ChatGPT, LLaMAWhat's included
| Service Tiers |
Starter
$490
|
Standard
$1,499
|
Advanced
$3,490
|
|---|---|---|---|
| Delivery Time | 2 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
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 | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$60Frequently asked questions
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SZ
Saul Z.
May 16, 2026
Looking for AI Developer to Build Lindy Bot That Transfers Testimonials to Senja.io
Loved working with Alex. Highly recommended.
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Iuse P.
Apr 5, 2026
Python Developer to script counting/identifies how many of our images appear across 3 sites.
OT
Omar T.
Mar 21, 2026
Google Sheets Integration with OpenAI for Automated Data Analysis and Scoring
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DeVaughn B.
Mar 16, 2026
Digital Signal Programming Advanced Task Windows 10
Alex is a good DSP Developer he must have 5 stars for effort as he developed solutions in 24 hour windows and even worked on a project before he was hired for it this is someone who is great to work with. However with Alex you want a lot of details included specific task breakdown as much as possible recommend hiring the support of a Systems Developer or Systems engineer so task process is clear and to the point. Alex is solid and among the top guys for DSP programming on Upwork
DS
Daniel S.
Feb 18, 2026
Prompt Engineer/NLP Specialist for Contextual Email Search from MBOX File
Alexandr was fantastic to work with. Extremely knowledgeable and polite. A massive resource.
About Alexandr
n8n & AI Automation Expert | RAG Chatbots, AI Agents, Python
89%
Job Success
Almaty, Kazakhstan - 3:13 am local time
What I do:
• AI agents & RAG chatbots (OpenAI, Claude, LangChain)
• Workflow automation (n8n, Make, Zapier) + custom Python
• Web scraping & data extraction
• API integrations & backend (FastAPI, Django, PostgreSQL)
Message me or book a quick call — I'll tell you straight whether I can help and how I'd do it.
Steps for completing your project
After purchasing the project, send requirements so Alexandr can start the project.
Delivery time starts when Alexandr receives requirements from you.
Alexandr works on your project following the steps below.
Revisions may occur after the delivery date.
Fit-Check & Baseline
Run quick evals on sample Q&A to measure accuracy, latency, cost. Deliver short report with metrics.
RAG Pipeline Setup
Ingest client docs into vector DB, build retrieval + reranker, connect to LLM. Provide working API / demo.