I’m looking for a Shopify-compatible AI chatbot that can respond to customer questions using a structured knowledge base — like a TXT or CSV file — rather than relying only on what’s in Shopify’s product listings.
Many of my product options and configurations are managed through a third-party product options app, so I can’t rely on Shopify’s native catalog alone. I need a bot that can:
Import and reference external data (ideally via TXT or CSV)
Respond only using the content I provide, without making things up or rewording
Follow a consistent format with specific titles and URLs (not summaries or paraphrases)
Be powered by something like ChatGPT, so it can follow clear instructions
Integrate with my Shopify storefront
Here’s the thing — I’ve already been able to get this working exactly how I want using ChatGPT directly , but none of the Shopify app store bots I’ve tried so far come close to that level of control or reliability. They often lack file upload support, or they try to guess and summarize — which just doesn’t work for what I need.
If anyone out there has found a solution — app, workaround, or even a custom integration — that can do this kind of knowledge-based chatbot well inside Shopify, I’d love to hear about it.
Or reverse this and find a service with a shopify integration instead of scouring through apps.
If your already using chatgpt look for a service to turn gpts into a chatbot, or just outright embed it into the website etc.
Or if you need it built custom and have a real budget reach out by PM or request that I PM you.
Does not exist, LLMS are probabilistic based.
Expecting no mistakes from a juiced up adlibs generator makes for bad policy, or impossible feature requirements that get fooled by marketing hype.
If you must have deterministic output you need to use a if/then else type of chatbot system and hand setup up all the quetions and answers.
For the external data, are they product specific? (each product has its own data). If not, most chatbots support certain knowledge injection. e.g. our chatbot, Shoply AI support pages/blogs/custom knowledge and external URLs for store knowledge injection.
If they are product specific, you could consider import them as metafield for each field. Then our chatbot can use the metafield to answer product specific questions.
" * Respond only using the content I provide, without making things up or rewording" - from our experience, if you indeed have related information provided as context, then ChatGpt usually answer well. If not, there is a slight chance of hallucination. With proper prompting it will be less an issue.
Kind of. Basically you have, as an example, Color 1, color 2, color 3. (there are acctually over a thousand). And color 1 is in Product A,B,C, and D. Color 2 is only in Product B and D. color 3 is in product B,C,andD. That is the basic version of how specific they are. I tried Shoply AI and it had the same issues as all the others. I do already have the colors in the meta field of each one for search purposes… That may work… Yes, Chatgpt will answer well, but not the AI chatbots here on shopify.
If the color information is stored directly in the product metafields or as a product variant, we can easily use it for search filters or to answer product-specific questions. However, if that information is kept in a separate file mixed with various products, it becomes more challenging — especially for most chatbots.
That’s because searching through product data is quite different from searching general store content, and the two are often optimized separately.
For example, in Shoply, we maintain two separate indexes: one for products and another for all other store content. Product data is typically well-structured, while other content is not. Searching across both can be difficult, especially at scale with hundreds or thousands of products.
For this reason, it’s generally much more effective — and chatbot-friendly — to store product-specific details, like colors, directly within the product metafields.
For privacy reason Shoply won’t automatically allow accessing all metafields, as some stores may store private information in them. We can work with you to whitelist the fields that you want the Chatbot to access. Should be fairly easy.
A lot of information about your e-shop is already being stored in the product metadata, your orders etc. We can access that data with your permission (1 click) and use it privately without knowing anything about your customers if you wish.
How about Chaterimo - AI customer service for Shopify by Chaterimo | Shopify App Store and instead of using shopify product download via API, use your own Google shopping XML feed with meta fields (product details). In Chaterimo you can also select ChatGPT/Gemini/Claude and modify your instructions (system prompt) so that LLM can output what you desire.
Hi @utkilts - We are building a solution for this using knowledge graphs at the node mind (https://thenodemind.com/). Most Shopify bots sit on top of the product catalog and try to infer answers. That breaks down fast when your real logic lives in external files or a third-party options app.
Node Mind is built to solve that gap.
It ingests TXT / CSV as structured knowledge (not summaries)
Answers are strictly grounded in what you provide
You can enforce exact formats, titles, and URLs
If something isn’t in the data, the bot doesn’t guess
The AI (ChatGPT-class models) sits on top of this knowledge layer — it doesn’t replace it. If you’re interested, happy to share how a lightweight trial works using one of your existing files.
Hey @utkilts, I totally understand your goal because you want the bot to only repeat what’s in your data without guessing or rewording. Most chat tools onboard with AI are built to interpret, so unless you tie them to a retrieval system that strictly pulls answers from your structured files or fields, they’ll default back to trying to paraphrase.
A lot of Shopify setups that get closer to what you want end up putting key info into structured schema like metafields or metaobjects that are exposed to the bot. The key is making sure the bot you choose can read those fields instead of just indexing the normal product content. Some bots skip certain fields unless you explicitly map them.
Since you already have the color info in metafields, the next question to narrow this down is how those values are stored (plain text vs structured options) and where you want the bot to show responses (on product pages for shoppers or in support chat). That will help figure out the simplest way to make a retrieval-only response work for your CSV/TXT data.