Free
$0Free plan available.
SupBot is an AI-powered support solution that allows users to instantly deploy AI support bots. It offers a user-friendly dashboard to train and deploy support bots in three steps: train the bot, test it live, and deploy the HTML script into your project or site. SupBot automates responses to routine questions, provides instant support 24/7, ensures consistent support trained on business data, reduces support costs, and offers contact retrieval and a ticketing system.
To use SupBot, train your bot by providing the necessary functional inputs, test the bot as needed, and deploy it by copying and pasting the provided script into your website or project. You can also manage visitor support requests through the integrated ticketing system.
SupBot is an AI-powered support solution that integrates easily into any website.
You can get started for free by creating an account and launching your first SupBot.
The free plan includes 100 monthly messages. The Standard plan costs $15/month for one bot, and the Premium plan costs $45/month for five bots.
Click the chat icon in the bottom right corner to request human assistance and submit a support ticket.
If a customer requests to speak with a human, a ticket containing the conversation history will appear in your dashboard.
SupBot utilizes OpenAI technology to build custom support bots trained according to your specific inputs.
Free plan available.
Use these comparison pages to understand the trade-offs between the models most relevant to SupBot.
Compare GPT 5.4 and GPT 5.4 Pro across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
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Compare GPT 5.5 and Claude 4.6 Opus across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare GPT 5.5 and Claude 4.6 Sonnet across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
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