Chatclient

1
5 0 Reviews 1 Saved
Introduction: Chatclient is a custom AI agent builder that enables you to train ChatGPT on your own data and integrate a chat widget into your website. It assists businesses in creating, embedding, and deploying AI agents for customer support, lead generation, and user engagement. By uploading documents or linking content, you can build an agent capable of answering questions based on your specific information.

Chatclient Product Information

What is Chatclient?

Chatclient is a custom AI agent builder that allows users to train ChatGPT on their own data and easily add a chat widget to their website. It helps businesses build custom AI agents, embed them on their website, and use them for customer support, lead generation, and user engagement. Users can upload documents or link their content to create an agent that can answer questions about the content.

How to use Chatclient?

To use Chatclient, import your data by uploading files (PDFs, TXT, CSV, DOCX), pasting text, or adding a link to your website. Customize the behavior and appearance of your agent, then embed it on your website using the provided div or chat bubble code, or use the API to interact with your agent.

Chatclient's Core Features

  • Custom AI agent training
  • Website embedding
  • Integration with other tools
  • Multiple data source import
  • Customizable appearance
  • Whitelabel option
  • Privacy and security
  • Auto-retrain
  • Multi-language support

Chatclient Use Cases

#1 Reduce customer support costs
#2 Generate and qualify leads
#3 Provide personalized user experiences
#4 Create AI personas for user engagement
#5 Add AI agents to websites and mobile apps

FAQ from Chatclient

What is Chatclient? +

Chatclient is a custom AI agent builder that trains ChatGPT on your data and lets you easily add a chat widget to your website. Simply upload your documents or link your content to create an agent that answers questions based on your specific information.

What should my data look like? +

You can upload one or multiple files (PDF, TXT, CSV, DOCX), paste text directly, or provide a link to your website for scraping.

Is there a free plan? +

Yes, signing up for Chatclient provides access to a free plan, which includes 15 message credits and 1 agent. This allows you to test the platform and determine if it meets your requirements.

Can I give my agent instructions? +

Yes, you can customize agent settings by assigning a unique name, defining personality traits, and providing specific instructions for how it should answer questions, such as restricting responses to a specific language.

Does it support other languages? +

Yes, Chatclient supports approximately 95 languages. You can provide source content in any of these languages and ask questions in any of them.

How can I add my agent to my website? +

You can embed a div or add a chat bubble to the bottom right of your website. After creating an agent, click "Embed on website" to get the code. You can also use the API to integrate your agent elsewhere.

How can we contact you? +

You can reach us via email at support@chatclient.ai or through our social media channels.

Chatclient Pricing

Free

$0

Free plan available.

Related Model Comparison Pages

Use these comparison pages to understand the trade-offs between the models most relevant to Chatclient.

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.

Compare GPT 5.5 and GPT 5.4 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 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.