AI Agent on the website
1. Project Goal
It is necessary to create an AI agent for the website mold.com.ua that will automatically respond to customers' main questions about products, orders, delivery, payment, and product usage.
The main task of the agent is to reduce the workload on managers, speed up responses to customers, and help buyers transition to ordering more quickly.
2. What the AI Agent Should Be Able to Do
The agent should answer customers' questions about:
- Orehova molds products
- Product availability
- Mold characteristics
- Material and safety of silicone
- What molds are suitable for
- How to use the molds
- How to care for the molds
- Delivery within Ukraine
- International delivery
- Payment
- Shipping times
- Returns / exchanges
- How to place an order
- Where to find the required mold
- What additional products can be purchased with the order
3. Main Logic of Operation
The AI agent should work as a buyer's assistant.
It does not just answer questions but helps the customer:
- find the right category of products;
- understand if the mold is suitable for their task;
- get a brief usage instruction;
- proceed to purchase;
- add related products;
- contact a manager if the question is complex.
4. Sources of Information for the Agent
The agent should take answers only from an approved knowledge base.
The knowledge base should include:
- Website FAQ.
- Descriptions of product categories.
- Descriptions of main products.
- Instructions for using silicone molds.
- Information about delivery.
- Information about payment.
- Return / exchange policy.
- Information about international delivery.
- Data on material and safety of silicone.
- Typical questions from Instagram / KeyCRM.
- Prepared response scripts for managers.
- Links to main categories and products.
5. Important Limitations
The agent must not invent information.
If it does not know the exact answer, it should write:
"I will clarify this question with the manager"
or
"For an accurate answer, it is better to contact the manager."
The agent must not independently invent:
- exact delivery times if they are not in the database;
- product availability if there is no integration with stock;
- discounts that are not on the website;
- warranties that the company does not provide;
- medical or technical properties of the material without confirmation.
6. Communication Tone
The style of responses should be:
- polite;
- warm;
- professional;
- simple;
- without unnecessary "water";
- in the style of the Orehova molds brand.
The agent should communicate in Ukrainian by default.
It is preferable to provide the possibility of responses:
- in Ukrainian;
- in Russian;
- in English.
7. Examples of Questions the Agent Should Answer
About Products
- Which mold is suitable for mousse dessert?
- Can the mold be used for chocolate?
- Can the mold be placed in the freezer?
- Can the mold be used in the oven?
- What is the size of the mold?
- What is the volume of the mold?
- What silicone is the mold made of?
- Is silicone safe for food?
- How to remove the dessert from the mold?
- How to wash the silicone mold?
About Orders
- How to place an order?
- What payment methods are available?
- Can I pay upon receipt?
- When will you ship the order?
- Which delivery service do you use?
- How much does delivery cost?
- Is there international delivery?
- Do you ship to Poland / USA / Europe?
About Product Selection
- Recommend a mold for a bento cake.
- I want to make chocolate figures, what should I choose?
- What molds are the most popular?
- What should I buy with the mold?
- What dyes are suitable?
- What chocolate is best to use?
8. Functionality on the Website
The AI agent should be placed in the form of a chat on the website.
It is preferable to implement:
- A chat button in the bottom right corner of the website.
- A welcome message.
- Quick buttons with popular questions.
- The ability to write your question.
- Links to products and categories.
- Transfer of complex questions to the manager.
- Collection of customer contacts if consultation is needed.
- Display of chat on desktop and mobile.
9. Quick Buttons in the Chat
When opening the chat, it is preferable to show buttons:
- Select a mold
- Delivery and payment
- International delivery
- How to use the mold
- Where is my order
- Contact the manager
10. Transfer to the Manager
The agent should transfer the dialogue to the manager if:
- the customer wants to place an order through the manager;
- the customer asks about specific availability if there is no integration with 1C/KeyCRM;
- the customer has a complaint or issue;
- the customer wants a custom order;
- the customer asks about wholesale conditions;
- the agent does not know the exact answer.
When transferring to the manager, the agent should ask for:
- name;
- phone or email;
- a brief description of the question.
11. Integrations
It is preferable to provide integration with:
- OpenCart — for operation on the website.
- KeyCRM — for transferring dialogues to managers.
- 1C / KeyCRM — for obtaining current availability and prices, if technically possible.
- Google Analytics / Meta Pixel — for tracking the effectiveness of the agent.
At the first stage, a simple version can be made without full integration with 1C, but with a knowledge base and links to products.
12. What the Agent Should Collect for Analytics
It should be possible to see:
- how many customers opened the chat;
- how many asked questions;
- what questions are the most frequent;
- how many dialogues were transferred to the manager;
- how many customers went to the product;
- how many customers added a product to the cart after the chat;
- what questions the agent could not close;
- what answers need improvement.
13. Knowledge Base
The developer should prepare or help prepare the structure of the knowledge base.
Desired format:
- questions;
-
Good day, I am interested in your proposal. I would be happy to collaborate. Cost calculations and timelines will be discussed after the details.
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Good day.
I am ready to take on the project. I have implemented similar solutions — RAG agents with a knowledge base, integrations with OpenCart, KeyCRM, GA4, and Meta Pixel.
Stack:
— RAG-pipeline (embeddings + Qdrant/Pinecone vector store + LLM responses only from context) — addresses the key requirement: the agent does not fabricate answers, and in the absence of a response, it forwards to the manager;
— LLM: GPT-4o-mini or Claude Haiku (balance of quality and token costs), automatic language detection (UA/RU/EN);
— widget for OpenCart via JS script (without touching the core), quick buttons, direct links to categories/products, responsive;
— transfer to KeyCRM via API with name, contact, dialogue extract, reason tag;
… — GA4 + Meta Pixel events (chat_open, message_sent, escalated, link_clicked, etc.);
— admin analytics panel with all metrics from P.12 (top questions, unanswered questions, conversions).
I will help with the structure of the knowledge base — you provide the raw content (FAQ, manager scripts, Instagram questions), I will handle processing and vectorization.
What is NOT included in the basic estimate:
— live sync with 1C/KeyCRM for availability and prices (you mentioned that it can be done without at the start);
— the cost of API tokens is your operational expense (approximately $20–60/month).
Please write in private messages, I would be happy to discuss the details.
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1973 17 0 1 I have over 8 years of experience in e-commerce development and architecture of complex integrations, including platform synchronization with CRM systems. Previously, I successfully implemented similar omnichannel solutions for product niches with extensive catalogs and specific product characteristics (materials, volumes, heat resistance). I will deploy a stable chat widget, fully adapted for desktop and mobile, configure the logic of quick buttons (form selection, delivery), and build a knowledge base architecture based on your FAQs and scripts. The basic implementation of the chat with KeyCRM integration and a structured knowledge base will take 20 days. Let's discuss the technical details in the chat.
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1315 7 0 Good day.
I am ready to take your project into work.
I can develop a chat agent for your website with a knowledge base and a function to transfer to a manager.
Message me privately, and we will discuss all the details and choose the best solution for you.
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72 I reviewed your website mold.com.ua and am ready to create an AI agent that will reduce the workload on managers.
The AI manager will be able to automatically respond to customers according to the store's knowledge base and the sales funnels that we will set up.
I have extensive experience working with OpenCart and KeyCRM. I will be able to set up the integration of the AI manager with your website's database and transfer requests to the CRM system.
There is also the possibility of mass analysis of current and new dialogues.
Please write in private messages, and we will arrange a consultation.
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1168 7 0 Hello! My name is Nikita. I have been implementing AI solutions in paid advertising and automating marketing processes for over 2 years, working with Google Ads, Meta Ads, and TikTok Ads.
✅What you get when working with me:
— AI-enhanced advertising strategy instead of chaotic launches
— automation of analytics and control of project economics
— systematic scaling based on data and AI tools
📈I work with projects of various scales and use AI for faster analysis of results, finding growth points, and optimizing advertising processes without unnecessary costs.
I am ready to discuss your tasks and offer a practical plan for implementing AI in your project's advertising.
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8817 27 0 1 I have experience in developing AI chat agents with RAG architecture (OpenAI API + knowledge base), integrating them into websites and e-commerce projects. I can implement an AI consultant for Orehova molds: working with FAQs and the catalog, providing answers only from the knowledge base, multilingual support (UA/RU/EN), product selection scenarios, transferring complex dialogues to a manager, and lead collection. I will create a chat widget for the website with quick buttons, links to products, and dialogue analytics, as well as lay the groundwork for integration with OpenCart and KeyCRM. I am ready to discuss the MVP and system architecture.
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726 9 1 Hello! Having studied your project with great interest, I am ready to start working on it. Let's discuss the details to achieve the best result.
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3092 11 0 Good day! I am developing in Python! I am ready to execute. Write to me - we will communicate.
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432 1 0 Hello! I am creating an intelligent assistant for mold.com.ua that will know everything about your forms: from the safety of silicone to the nuances of delivery to the USA.
I am implementing the project on Make.com/n8n + OpenAI with integration into KeyCRM. The AI agent will not only answer FAQs but will guide the customer to purchase through quick buttons and product recommendations. The bot will operate strictly based on your knowledge base, and in complex cases, it will instantly transfer the dialogue to a manager with all the contacts.
You will receive warm, human service 24/7 and automatic unloading of the team.
Please let me know if you already have a ready FAQ structure or if you need help in forming it for the knowledge base?
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95606 1272 1 10 Hello. I have extensive experience with Python/React. Do you have a chat design?
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2380 8 0 Hello, I am ready to develop the necessary AI agent for you and add it to your website. I have extensive experience with automations using AI, feel free to contact me to discuss the details.
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2930 8 0 1 Hello. The task involves deploying an AI agent based on vector search (RAG) with an API integration for OpenCart and KeyCRM. I will write the backend in Python (response speed
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2848 17 0 1 Hello, Yevhen!
The task is very well described. I have done similar agents before. I can integrate with both 1C and KeyCRM to obtain current availability and prices.
It is also clear how the agent should work, and everything is clearly outlined.
I will definitely help prepare the knowledge base; we can also run previous conversations (if there are any in messengers, for example) and calls through AI for initial question and answer formation.
Overall, it's a good project.
… In terms of deadlines, it will take about 30 days to complete "turnkey," considering testing on your side (this is a mandatory part, which is estimated to take 12-15 days).
Regarding the cost, it will be around $1000, but we should discuss in more detail what we are integrating with and your overall non-functional expectations from the AI agent's work.
Write to me, and we will discuss the system in more detail; I will provide a precise proposal.
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716 4 0 I can implement this project not as a regular chat on the website, but as a full-fledged AI sales consultant that will work towards business results. The main advantage of my approach is that the agent will not just answer customer questions, but help them move to purchase faster, select appropriate forms, recommend complementary products, and correctly pass complex requests to the manager. This will significantly reduce the burden on the support team and increase the website's conversion rate.
I have a good understanding of the logic of eCommerce projects and the importance of stable AI performance without fabricated answers. That’s why the agent will operate solely based on an approved knowledge base, without fantasizing about product availability, delivery times, or non-existent guarantees. If data is insufficient, the system will correctly transfer the dialogue to the manager while preserving the context of the conversation and the customer's contacts.
I will pay special attention to the convenience of administration. The knowledge base will be structured in such a way that it can be easily updated without complex technical changes. I will also implement multilingual support, adaptation for mobile and desktop, integration with OpenCart, KeyCRM, analytics, and the ability to scale functionality in the future. As a result, you will receive not a test AI module, but a ready tool for automating communication and increasing sales.
Project implementation plan:
1. Analyze the website structure, product categories, and current scenarios of manager operations.
2. Formulate the structure of the knowledge base for the correct operation of the AI agent.
… 3. Prepare FAQs, instructions, information about delivery, payment, returns, and international shipments.
4. Add logic for product selection and recommendations for complementary products.
5. Configure the AI model with restrictions on fabricating information.
6. Implement the transfer of complex dialogues to the manager.
7. Collect customer contact data in the chat.
8. Develop a chat widget for the desktop and mobile versions of the website.
9. Add quick buttons and starting scenarios.
10. Integrate with OpenCart and KeyCRM.
11. Connect Google Analytics and Meta Pixel analytics.
12. Test dialogue scenarios and correct responses.
13. Launch the first version and optimize based on real customer inquiries.
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3067 11 0 1 Good day.
I have experience in developing AI assistants for websites, integrating with CRMs, and building RAG systems based on structured knowledge bases. For your case, it makes sense to create the agent not as a "regular chat," but specifically as a buyer's assistant with control over information sources and the transfer of complex cases to a manager.
According to the specifications, I see the correct emphasis on ensuring that the agent does not fabricate answers. This can be implemented by working only with an agreed knowledge base + fallback logic when the model is unsure of the answer. Then the agent either provides an answer from the source or transfers the client to the manager without "hallucinations."
I envision an optimal implementation in several stages:
first, an MVP with a knowledge base, FAQ, products, delivery, and chat integration on the website,
then connecting KeyCRM, analytics, and if necessary, stock/prices.
…
It can be implemented:
a chat for desktop/mobile,
quick buttons,
multilingual support,
transfer of dialogue to the manager,
contact collection,
analytics on questions and conversions,
links to products and categories in OpenCart.
For the knowledge base, it is better to prepare a proper structure right away so that it can be maintained without a developer. For example:
questions,
answers,
category,
keywords,
links to product/category,
languages.
It is also worth immediately incorporating logging of the agent's "failed" responses — this greatly helps to quickly improve quality after launch.
After familiarizing myself with OpenCart, the catalog structure, and current materials, I will be able to propose a specific architecture, stack, and MVP launch plan.
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919 4 0 Good day, Yevhen, I have worked on a similar project, but it was related to the hotel business. Let's break it down step by step:
1. For general information, RAG will be used (it can be external, such as the GPT API, or internal if the server allows it). It is needed for answering general questions from the FAQ, payment, delivery, etc.
2. For products, it is better to use vector search (for example, Qdrant) or simply semantic search. Then, an agent tool is used that queries the database, retrieves product information, and based on this information, provides a response regarding the product. This can also be implemented through an mcp server.
The implementation uses the Python Async programming language. There are many different options for RAG, and it is advisable to test 2-3 for your business (Haystack/RAGFlow/LangChain (+ LangGraph)). For agent management and validation — Pydantic AI. For vector search — Chroma/Qdrant.
I would be happy to work with you.
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234 Hello. I will complete everything quickly and efficiently, according to the specifications. Write to me, I have experience.)
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6589 28 0 I will create an AI agent based on the RAG architecture: I will upload your knowledge base (FAQ, product descriptions, delivery, payment, returns), and set up escalation to a manager for unknown questions. The agent will respond in Ukrainian by default, with support for Russian/English. I will integrate it as a chat widget on the website or via API.
What CMS does the site mold.com.ua use, and is there already a ready-made knowledge base in a structured format, or does it need to be built from scratch?
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