AskBrew vs Chatbase: which fits your support team?

What both tools do the same way

Both are no-code. You upload PDFs and documents, point the tool at your website, and it builds a searchable index from that content. Both then answer customer questions from the index rather than from the model's training data, which is what keeps answers specific to your business.

Both install on any website with a script tag, both let you set the assistant's tone and appearance, and both surface analytics on what customers are asking.

• —Train on documents, website content, and written notes
• —Answer from your content rather than general model knowledge
• —Embed on any site with a single snippet
• —Customise the widget's look, tone, and welcome message

The difference that matters most: what happens when it doesn't know

Every retrieval-based assistant faces the same moment several times a day. A customer asks something your knowledge base does not cover, the retrieval step comes back with weak matches, and the model has to decide what to do with them.

The failure mode is a confident answer assembled from loosely related passages. It reads well, the customer believes it, and you find out when they complain. Grounding reduces this but does not eliminate it — the standard guidance is to give the assistant explicit permission to say it does not know, and to route the question onward rather than guess.

AskBrew is built around that moment specifically. Every answer is recorded with whether it was actually answered, a confidence score, and the retrieval trace behind it. When the assistant cannot answer, it says so, offers a handover to your team if you have that enabled, and the question is written to a list of unanswered questions in your dashboard.

That list is the point. It is a queue of things your customers wanted to know and your content did not cover — which is the most direct signal you will ever get about what to write next. Answer the question, add it as a note, retrain, and the gap closes.

• —Answers are marked answered or unanswered, not silently returned
• —Unanswered questions collect in a dashboard queue you can work through
• —Each answer stores its retrieval trace, so you can see which sources produced it
• —Visitors see linkable citations; internal document names stay private to your team

Questions about your content vs questions about the customer

"What is your returns policy?" is a content question. Any tool trained on your policy page will answer it. "Where is my order?" is not — the answer lives in your store, it is different for every visitor, and getting it wrong for the wrong person is a data breach rather than an embarrassment.

AskBrew handles the second kind through Actions. Your server vouches for who the visitor is with a signed token or HMAC hash, AskBrew verifies that signature, and only then are identity-gated tools offered to the model at all. An unverified visitor never gets those tools in the first place, so there is nothing for a persuasive prompt to talk its way into.

For Shopify stores this is a one-click connection rather than custom work. Any other backend is wired up as a custom HTTP endpoint you define, with the auth header encrypted at rest and a timeout you set.

How each one gets better over time

Both tools show you what customers ask. The difference is what you are expected to do with it.

The common pattern is a transcript log and a chart of popular topics, which tells you what is being asked but not where the assistant fell short. AskBrew separates the two: conversations are there to read, but the queue you work from is the unanswered questions plus the answers customers marked unhelpful. Those two lists are the ones that change the product's accuracy when you act on them.

Our recommendation

For a support team whose customers are on their website, we think AskBrew is the better choice, and the two reasons above are why.

The first is that most of the tickets worth deflecting are not content questions. "Where is my order?" is the single most common message an ecommerce support inbox receives, and a content-only assistant cannot touch it — it will answer beautifully about your returns policy and then hand the actual volume straight to your team. AskBrew answers it, safely, for a customer your own server has vouched for.

The second is that a wrong answer costs more than no answer. An assistant that guesses turns a deflected ticket into an angry one, and you only find out later. AskBrew is built to say it does not know, log the question, and hand over — which is slower to look impressive in a demo and considerably cheaper to run.

Chatbase is a capable product and if you need WhatsApp and Messenger coverage it is the sounder pick. Short of that, we would back ours.

Do not take our word for it. Load the ten questions your team actually gets, including the awkward ones nobody has documented, into both. The tool that admits what it does not know is the one your customers will end up trusting.