You will get a private offline AI document assistant for sensitive files
Top Rated
Top Rated
Project details
I build custom offline AI document workflow applications for professionals who work with sensitive files and need structured, repeatable document processing.
This project is focused on AI engineering, not model training. I can create a privacy-first desktop app that processes documents and transcripts locally using a local LLM or a private API-based setup. The system can include file upload, ZIP batch processing, PDF/DOCX/TXT extraction, audio transcript handling, document classification, prompt routing, structured summaries, metadata extraction, knowledge graph logic, final report generation, and export to TXT, DOCX, PDF, or JSON.
The workflow can be adapted to different languages, document types, report templates, and domains such as legal, medical, compliance, insurance, HR investigations, or research.
For local LLM setups, the model can be bundled with the app or downloaded during first setup. After setup, documents can be processed locally without sending sensitive files to cloud AI services.
I can package the solution for macOS Apple Silicon or Windows depending on your requirements.
This project is focused on AI engineering, not model training. I can create a privacy-first desktop app that processes documents and transcripts locally using a local LLM or a private API-based setup. The system can include file upload, ZIP batch processing, PDF/DOCX/TXT extraction, audio transcript handling, document classification, prompt routing, structured summaries, metadata extraction, knowledge graph logic, final report generation, and export to TXT, DOCX, PDF, or JSON.
The workflow can be adapted to different languages, document types, report templates, and domains such as legal, medical, compliance, insurance, HR investigations, or research.
For local LLM setups, the model can be bundled with the app or downloaded during first setup. After setup, documents can be processed locally without sending sensitive files to cloud AI services.
I can package the solution for macOS Apple Silicon or Windows depending on your requirements.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI-Enhanced Classification, Automatic Speech Recognition, Conversational AI, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Models
LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$800
|
Standard
$2,400
|
Advanced
$5,500
|
|---|---|---|---|
| Delivery Time | 10 days | 21 days | 45 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
+$75
Extra document type
(+ 3 Days)
+$75
Report export
(+ 3 Days)
+$100Frequently asked questions
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FA
Fahad A.
Jul 2, 2026
30 minute consultation
YG
Yunna G.
Feb 12, 2026
RAG pipeline for Albanian technical documentation (Telecom)
Yevgenia did an outstanding job with the RAG feasibility study for our Albanian documentation. Her technical background in CS and expertise with local LLMs were evident. The report was professional, insightful, and delivered on time. Highly recommend for complex AI/ML tasks!
About Yevgenia
Top Rated Plus AI/ML Engineer | Offline LLM App RAG Knowledge Graph AI
100%
Job Success
Vyshhorod, Ukraine - 5:41 am local time
AI/ML Engineer and Databricks Certified Generative AI Engineer specializing in secure, offline AI systems for sensitive data and domain-specific workflows.I am a Ukrainian freelancer working remotely from Europe.
I combine AI/ML engineering expertise with 16 years of legal experience in intellectual property and business-related legal matters. This gives me a strong advantage when building AI systems for sensitive documents, legal workflows, compliance-heavy environments, and domain-specific decision support.
My main focus is building local AI applications that run fully offline using open-source base LLMs, without relying on cloud APIs, external databases, or model fine-tuning. Instead, I design strong engineering pipelines around the model: document processing, domain logic, knowledge graph structures, prompt orchestration, validation steps, and structured report generation.
This approach is especially valuable for legal, medical, finance, and enterprise environments where data privacy, cost control, and local execution are critical.
My Core Expertise:
Offline LLM Applications
Building AI tools that run locally on macOS, Linux, or Windows using open-source models such as Llama, Mistral, Qwen, and other local LLMs.
Knowledge Graph-Based AI Pipelines
Designing structured AI workflows that use knowledge graphs, document metadata, domain rules, and multi-step reasoning pipelines to improve output quality without fine-tuning.
Privacy-First AI for Sensitive Documents
Creating systems where documents, prompts, summaries, and generated reports remain fully local, reducing data exposure and cloud dependency.
Document Intelligence & Structured Reporting
Processing complex, domain-specific documents and generating summaries, structured outputs, and final reports tailored to professional workflows.
Full-Stack AI Engineering
Building complete AI applications from backend pipeline design to desktop packaging, FastAPI services, local model integration, and deployment-ready solutions.
Tech Stack:
AI/ML: Python, PyTorch, Hug Face, LangChain, llama.cpp, Ollama
Local LLMs: Llama, Mistral, Qwen, GGUF models, quantized models
Data & Engineering: FastAPI, Docker, SQL, MLflow, Databricks
Optimization: Model quantization, local inference optimization, Apple Silicon / Metal acceleration
Applications: Offline AI tools, knowledge graph pipelines, document processing systems, desktop AI applications
Education & Certifications:
MSc in Computer Science, Data Science & Analytics – Woolf University
Databricks Certified Generative AI Engineer
Top Rated Plus Freelancer on Upwork
One of my recent long-term projects started as a request to migrate an online AI prompt into a local offline application for forensic document assessment. The final solution evolved into a privacy-first desktop AI system for sensitive professional documents, using a local open-source base LLM, custom document processing, document classification, knowledge graph structures, prompt orchestration, validation logic, structured reporting, and secure local deployment - without cloud APIs , databases and model fine-tuning.
If you need a secure, offline AI solution that works with sensitive documents and runs full locally on your own hardware, I can help design and build a practical system tailored to your workflow.
Steps for completing your project
After purchasing the project, send requirements so Yevgenia can start the project.
Delivery time starts when Yevgenia receives requirements from you.
Yevgenia works on your project following the steps below.
Revisions may occur after the delivery date.
Project requirements review
I review your document types, workflow, target platform, privacy needs, output format, and local LLM setup requirements.
Workflow and architecture design
I design the document pipeline: file upload, text extraction, classification, prompt routing, LLM processing, knowledge graph logic, and exports.