Chatbase.me VS AgentX

Chatbase.me

Interactive chat bot trained on your knowledge base to help you engage with your website users. Chat with document and pdf.

AgentX

24/7 AI chat support based on your support documentation

Chatbase cover //
2024-03-17

Chatbase.me help you to train your knowledgebase on ai and use it on your website for customer support.

AgentX welcome screen //
2024-01-10

AgentX provides 24/7 customer chat support based on your support documentation. AgentX is ready to go in minutes and automatically tracks changes to your support documentation to ensure questions are answered with the most up to date information.

Chatbase.me

Website: chatbase.me
Pricing URL: -
$ Details: freemium $5.0 / Monthly (Basic Plan)
Release Date: 2024 January

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AgentX

Website: theagentx.com
Pricing URL: Official AgentX Pricing
$ Details: paid Free Trial $29.0 / Monthly
Release Date: 2024 January

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Chatbase.me features and specs

Chatbot: Yes
Chat with PDF: Yes
Livechat: Yes
Customer Support: Yes

AgentX features and specs

No features have been listed yet.

Category Popularity

0-100% (relative to Chatbase.me and AgentX)

Chatbase.me

AgentX

AI

71 71%

AI

29% 29

Chatbots

74 74%

Chatbots

26% 26

Customer Support

72 72%

Customer Support

28% 28

PDF Tools

100 100%

PDF Tools

0% 0

User comments

Share your experience with using Chatbase.me and AgentX. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, AgentX seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Chatbase.me mentions (0)

We have not tracked any mentions of Chatbase.me yet. Tracking of Chatbase.me recommendations started around Mar 2024.

AgentX mentions (1)

Ask HN: What have you built with LLMs?
As I was building LLM projects, I found I was re-implementing a new vector database for each one. So I built RagTag (https://ragtag.weaveapi.com), a vectordb/RAG as a service to make the process faster. This provides a CRUD interface to push and retrieve documents, which are automatically chunked and converted to embeddings. AgentX (https://theagentx.com), an LLM chat support app is one of the projects I built... - Source: Hacker News / 5 months ago