You will get Production-Ready RAG Assistant (LangChain / LlamaIndex / Pinecone)
Project details
Build a Production-Ready RAG Assistant (LangChain/LlamaIndex/Pinecone)
💲 Basic — $250
Included
• Embeddings setup (OpenAI / HuggingFace)
• Vector DB setup (Pinecone / Chroma / DynamoDB / MongoDB)
• Basic-level semantic search
• Integration of 1 data source
• Simple API endpoint
• Test responses + quality validation
💲 Standard — $500
Included
• Full RAG pipeline
• Cleaning + splitting + chunking
• LangChain or LlamaIndex pipeline
• Integration of up to 3 data sources
• Built-in memory
• Prompt optimization
• Simple UI (Streamlit)
• Quality validation + optimization
💲 Premium — $1000
Included
• Full production-ready RAG system
• Complex ingestion pipeline
• Pinecone optimization
• Guardrails: hallucination reduction
• Monitoring dashboard
• JWT/Auth
• API integration into their product
• 1 week of support
💲 Basic — $250
Included
• Embeddings setup (OpenAI / HuggingFace)
• Vector DB setup (Pinecone / Chroma / DynamoDB / MongoDB)
• Basic-level semantic search
• Integration of 1 data source
• Simple API endpoint
• Test responses + quality validation
💲 Standard — $500
Included
• Full RAG pipeline
• Cleaning + splitting + chunking
• LangChain or LlamaIndex pipeline
• Integration of up to 3 data sources
• Built-in memory
• Prompt optimization
• Simple UI (Streamlit)
• Quality validation + optimization
💲 Premium — $1000
Included
• Full production-ready RAG system
• Complex ingestion pipeline
• Pinecone optimization
• Guardrails: hallucination reduction
• Monitoring dashboard
• JWT/Auth
• API integration into their product
• 1 week of support
AI Algorithms
Large Language Model, Long Short-Term Memory Network, Transformer ModelAI Applications
AI Chatbot, AI Mobile App Development, Conversational AI, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, StreamlitAI Models
ChatGPT, GPT-3, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$250
|
Standard
$500
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 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.
Fast Delivery
+$400 - $1,700Frequently asked questions
About Kyrylenko
AI Dev Team Lead
Kyiv, Ukraine - 2:24 pm local time
Experienced Project Manager with a specialization in artificial intelligence projects. I am able to combine a deep understanding of AI technologies with a clear organization of processes to deliver business value in a timely and efficient manner.
Key skills:
Project management: Agile (Scrum, Kanban), Waterfall, hybrid approaches
AI/ML technologies: NLP, computer vision, generative models (GPT, BERT, Diffusion)
Tools: Jira, Asana, Trello, Git, MLflow, Figma, Intercom FIN AI automation.
Communication: meeting facilitation, presentations for stakeholders, writing technical and business documents
Analytics: setting success metrics (OKR, KPI), data analysis, A/B testing
Risk management: risk identification, reserve planning, change control
Experience.
Implementation of chatbots based on GPT-4 for customer support (reduction of response time by 40%)
Coordinating the development of computer vision systems for automating quality control in production
Developing roadmaps, managing a team of 4-7 engineers and analysts
Supporting Agile processes in the Data Science team
Preparation of technical specifications for machine learning models
Monitoring model performance, preparing reports for C-leve
Steps for completing your project
After purchasing the project, send requirements so Kyrylenko can start the project.
Delivery time starts when Kyrylenko receives requirements from you.
Kyrylenko works on your project following the steps below.
Revisions may occur after the delivery date.
Build Full RAG Pipeline
We create a full-featured system for searching and generating answers based on your documents.
Integrate Your Data Sources
We connect your documents and databases so the system works seamlessly with your own data.