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You will get custom chatbot (GPT) based on your documents / pdfs / websites / notion
Project details
You will get a custom Chatbot with GPT-3.5 to answer questions about your data. Answer clients' questions about your product based on product documentation, let employees ask questions of your internal company policies, or ask questions about any set of legal, financial or other documents. Behind the scenes, the documents are embedded in a vector store index for ultra-fast lookup, and GPT provides an easy-to-understand human interpretation, as well as links to the original source data to ensure accurate results and allow in-depth follow-up. Response time depends on the OpenAI API and is generally around 7-8 seconds.
Programming Languages
HTML & CSS, JavaScript, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, DesignWhat's included
| Service Tiers |
Starter
$400
|
Standard
$600
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 10 days | 10 days | 7 days |
Number of Revisions | 0 | 1 | 2 |
Design Customization | - | - | |
Content Upload | |||
Responsive Design | - | ||
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $150
Data prepration - minimal
(+ 1 Day)
+$200
Data prepration - medium
(+ 2 Days)
+$400
Data prepration - advanced
(+ 3 Days)
+$600Frequently asked questions
About Andrew
AI & Machine Learning | GPT Consulting, Data Science, Deep Learning
Nantes, France - 2:39 pm local time
- machine learning and deep learning models using Keras, TensorFlow, and PyTorch
- application of large language models (LLMs) such as GPT to tasks such as text labeling, text retrieval, and question and answering, integrating GPT with other resources such as web search with LangChain and LlamaIndex
- semantic search and vector store databases such as Pinecone, Weaviate, Qdrant, ElasticSearch
- text analysis through vector word embeddings models, topic and sentiment modeling, and ML
- causal inference and experimental design
- enterprise-focused solutions on cloud platforms such as AWS and Google Cloud
- Data visualization and data analytics platforms built on Flask, Gradio, Streamlit and FastAPI
My practical experience has been built around solid fundamental knowledge in machine learning, statistics, econometrics and economics. I mainly use Python, but have also coded in R and have basic knowledge of C++ (e.g. for a course I taught in Big Data and Finance at Baruch College (CUNY).
Previous clients ranging from OCEEF.org; Christal-IS, Newpricer; ghSMART & Co; to Astoria Analytics.
I completed my PhD in 2017 at New York University focusing on the machine learning of texts using vector embeddings and then spent three years as a postdoctoral researcher at the University of Geneva. I also completed a 5-course certification on "Machine Learning in Google Cloud", and have published in a number of academic journals including Socio-Economic Review, Political Analysis, and the Russel Sage Foundation Big Data in Political Economy.
Steps for completing your project
After purchasing the project, send requirements so Andrew can start the project.
Delivery time starts when Andrew receives requirements from you.
Andrew works on your project following the steps below.
Revisions may occur after the delivery date.
verify data source
I ensure that the data source is available and does not require additional preparation or cleaning beyond what has been purchased.
Custom domain/ other details
If you want to deploy the chatbot to a custom domain, we will need to discuss the details (usually requires about 15 minutes of work, although the changes can take up to 72 hours to fully take effect through the global DNS servers).