GPTbots

What are GPTBots?

GPTBots is a code-free platform for developing and managing AI agents tailored for businesses. Companies can combine large language models, internal knowledge, databases, tools, and business processes to create applications for intelligent customer service, sales development, enterprise search, or data analysis.

The platform offers SaaS, API services, implementation consulting, and private deployment options. It does not rely on a single model alone; instead, it allows organizations to choose different business or open models based on their specific needs, while also enabling them to manage knowledge, workflows, distribution channels, and operational data.

Core product capabilities

• Code-free Agent Builder: Configure roles, instructions, knowledge, tools, and dialogue logic through an interface.
• Corporate knowledge base: Import documents and business materials to enhance search capabilities for answering queries.
• Visual workflow: Organize models, decisions, tools, databases, and batch tasks using nodes.
• Multi-model management: Unified configuration for text, image, audio, embedding, and reordering models.
• Enterprise AI search: It connects internal knowledge, databases, and business interfaces to generate answers specific to the organization.
• Text2SQL and charts: Convert natural language questions into queries and generate visual results.
• Multi-channel distribution: Integrate the agent into websites, messaging tools, and enterprise applications.
• Operational analysis: View sessions, issue categories, sentiment, usage, and service quality.

Intelligent customer service

GPTBots can automatically answer pre-sales, after-sales, and internal service questions based on the company’s knowledge base, and they create a complete service cycle through categorization, emotion recognition, and human intervention. Their multilingual capabilities are suitable for customer service teams operating in different regions.

• Answer common questions based on product documentation, the help center, and policy responses.
• Identify the user’s intent and route the request to the appropriate process.
• Transfer to a human agent when the confidence level of the answer is insufficient or the rules are triggered.
• Use the order, logistics, or ticketing tools to check the real-time status.
• Analyze session topics, satisfaction, unresolved issues, and knowledge gaps.
• Publish the agent on websites, WhatsApp, Facebook, Telegram, and other platforms.

AI sales development

• Receive visitors through various communication channels and gather clues.
• Assess the quality of leads based on budget, requirements, industry, and timeline.
• Synchronize lead prospects and conversation summaries to CRM.
• Automatically answers questions related to products, solutions, and appointments.
• Identify high-value leads and notify sales staff to follow up.
• Conduct multilingual communication using the tone and content approved by the company.

Enterprise AI search

Enterprise search enables the unified use of knowledge scattered across documents, cloud storage, business systems, and databases for answering questions. The system offers suggestions for follow-up questions as well as the ability to create customized answers, but it is still necessary to maintain the source of important conclusions and respect relevant access controls.

• Connect to sources such as Google Drive, Notion, and Microsoft Word.
• Control access to the knowledge base based on organizational structure and member permissions.
• Use vector retrieval and reordering to improve relevance.
• Obtain real-time data through business tools, rather than relying solely on static documents.
• Anonymize personal information and implement content security screening.
• Recording issues, citations, feedback, and missing content is used for optimization.

AI data analysis

GPTBots allows users to query structured data using natural language, and it converts the results into charts or action recommendations. This feature helps to reduce the difficulty for business professionals in writing query statements; however, it is necessary to verify the definitions of the fields and the permissions for querying before using it in actual operations.

• Convert natural language questions into database queries.
• It supports handling business issues by associating multiple tables.
• Generate dynamic interactive charts based on the results.
• Embed the analysis nodes to be executed at scheduled times within the workflow.
• Generate explanations and subsequent recommendations for abnormal indicators.
• Restrict the agent to accessing only approved datasets.

Agent, Flow-Agent, and Workflow

Knowledge base functionality

• Upload a file or connect to an enterprise content source.
• Parse documents and perform segmentation, indexing, and vectorization.
• Assign member permissions to different knowledge bases.
• Configure the number of recalls, similarity, and reordering.
• Reuse the same knowledge in agents and workflows.
• Manage or query content through the knowledge base API.
• Track the points consumed by storage, indexing, and retrieval.

Models and built-in keys

The platform supports various models such as OpenAI, Claude, Gemini, ChatGLM, and Llama, and it also offers embedding, reordering, and audio services. Organizations can use the keys provided by GPTBots, or they can utilize keys obtained from the model providers themselves.

Workflows and tools

• Use start, end, model, decision, and batch nodes to combine processes.
• Invoke official tools, enterprise-customized tools, and external business capabilities.
• Choose organization, agent, or end-user authorization for the OAuth tool.
• Text, files, and structured data are transmitted between nodes through variables.
• Set fallback logic for failures, timeouts, and abnormal branches.
• After it is published, the workflow is triggered via API or channels.

How to create a corporate agent

1. Create an organization and define the single business objective that the agent is meant to address.
2. Choose Agent, Flow-Agent, or Workflow as the implementation method.
3. Configure roles, system instructions, response boundaries, and conditions for transferring to a human agent.
4. Upload the organized knowledge documents and set the search parameters.
5. Add the required models, databases, and business tools.
6. Use real-world problems to test correct answers, rejected responses, and abnormal paths.
7. Publish after configuring channels, permissions, logging, and content security.
8. Based on unresolved issues, user feedback, and ongoing cost optimization.

Enterprise launch process

1. Choose scenarios for which it is possible to measure accuracy, resolution rate, time taken, or conversion rate.
2. Identify the data sources, system owners, users, and compliance boundaries.
3. Create small knowledge bases and minimal viable processes using anonymized data.
4. Verify model responses, knowledge retrieval, tool invocation, and system writing separately.
5. Establish role permissions, key management, data anonymization, and audit mechanisms.
6. First, make it available to internal users or a small number of users, while retaining the option for manual intervention.
7. View logs, failed tasks, point consumption, and business metrics.
8. Expand channels, seats, and the scope of automation once the quality threshold is reached.

Which users are it suitable for

• Large and medium-sized enterprises that need multilingual intelligent customer service.
• Organizations that wish to create an internal search tool for knowledge.
• Teams that need to automatically filter and synchronize leads are in need of such capabilities.
• Managers who wish to query business databases using natural language.
• Products and operations teams that need to develop AI applications rapidly.
• Enterprise technical teams that need API, privatization, and implementation services.

Typical use cases

• The website’s customer service team answers questions about products and checks the status of orders.
• Employees search for systems, processes, technical documents, and project materials.
• Sales agents collect and evaluate leads on social media channels.
• Sales staff use natural language to analyze databases and generate charts.
• The IT service desk automatically routes issues and creates tickets.
• The workflow handles files in batches, categorizes content, and updates the system.
• Healthcare, e-commerce, education, and IT companies are developing industry-specific intelligent agents.

Product advantages

• It covers the entire lifecycle of an agent, from creation and deployment to operational analysis.
• It supports multiple models, reducing the risk of being locked in by a single model provider.
• Knowledge bases, databases, tools, and workflows can be used in combination.
• It supports code-free configuration as well as a fairly comprehensive set of developer APIs.
• The separation between model acquisition and governance can be reduced by using proprietary keys.
• It supports private deployment, model deployment, and enterprise implementation services.
• The channels include customer service, social media platforms, and enterprise collaboration tools.

Usage restrictions

• The subscription fees for Business and Enterprise plans are not explicitly listed in the public documentation.
• Models, indexes, storage, reordering, and tools each consume points.
• Even when using a custom model key, one still has to pay both the costs associated with the model provider and the platform service fees.
• Complex workflows require an understanding of variables, exceptions, and permissions; they cannot rely solely on no-code interfaces.
• The effectiveness of a knowledge base depends heavily on the quality of the documents, as well as on the parameters used for segmentation and retrieval.
• The statements and charts generated from data queries may contain errors in their presentation.
• For private deployments and enterprise implementations, a sales assessment is required, and the delivery timeline and costs are not fixed.

Subscription plan

The official documentation states that 100 points are equivalent to 1 US dollar, but the deduction rates vary depending on the service. The points purchased cannot be refunded or exchanged, and the subscription fees, taxes, and enterprise delivery costs shall be in accordance with the pricing details and settlement information provided.

Integral consumption type

Safety and compliance

The official website outlines the enterprise security capabilities such as ISO 27001, ISO 27701, and SOC 2 Type II; the platform also offers support for role-based permissions, encrypted storage, content filtering, and the anonymization of personal data. These certifications do not replace the customer’s own data risk assessment.

• Restrict access to the knowledge base, Agents, Workflows, and organizational settings based on job roles.
• The keys are managed by designated personnel and rotated regularly; they are not included in prompts or ordinary documents.
• Confirm the data processing area and retention policy before invoking external models.
• Anonymize personal information and implement review for sensitive content.
• High-risk writes, transactions, and decisions must require manual confirmation.
• Use logs and cost reports to identify abnormal calls and cost fluctuations.

APIs and Integration

• Provides API references for Agents, Workflows, and knowledge bases.
• It is possible to initiate conversations or run workflows from the enterprise system.
• It supports querying workflow results and managing knowledge bases.
• Enterprise data and services can be accessed through custom tools.
• Options for publishing or connecting are available via websites, Discord, WhatsApp, Slack, Zapier, and more.
• Google Drive, Notion, and document-based materials can serve as sources of knowledge.

GitHub and the open-source status

The GPTBots core platform, the enterprise knowledge base, and the hosting services are not open-source products. The official GitHub repository hosts a few browser extension projects; among them, AgentOne is licensed under the MIT license and allows for the use of custom agents while browsing.

Basic information

Recommendation score

4.5 / 5. GPTBots is suitable for companies that wish to unify their models, knowledge bases, tools, channels, and operational analytics; it offers a comprehensive set of functions. However, there are many items subject to subscription-based pricing, and the subscription costs are not fully disclosed – it is therefore necessary to estimate the total cost using actual load levels before going live.

Frequently Asked Questions

Can GPTBots be used for free?

Sure, the Free plan offers 100 points per month, which is suitable for testing and creating small prototypes.

What is included in the Business package?

It includes 10,000 points, up to 100 Agents and Workflows, a maximum of 10 publications, as well as 10 team seats; the subscription cost requires consultation with sales.

How much is the credit?

A one-time top-up of 1,000 points is equivalent to $10, and the validity period is one year; these points cannot be refunded or exchanged.

Can I use my own model key?

Yes. The cost for the model is paid directly to the model manufacturer, while GPTBots will still charge a small amount in platform service credits.

Which enterprise use cases are supported?

Key use cases include intelligent customer service, sales development, enterprise knowledge search, and natural language data analysis.

Is private deployment supported?

Enterprise offers private deployment, Agent development and maintenance, as well as consulting and implementation services; the specific scope is detailed in the project quote.

Can it be connected to an enterprise database?

Yes, it is possible to retrieve data using database capabilities, Text2SQL, and custom tools; however, permissions must be restricted and the query results must be checked.

Does GPTBots provide an API?

It provides APIs such as Agent, Workflow, and Knowledge Base, which can be used for enterprise system integration and automated triggering.

Is GPTBots open source?

The core platform is not open-source, but the official GitHub page hosts a few additional projects such as AgentOne.

What is AgentOne?

AgentOne is an official browser extension under the MIT license; it allows users to connect custom agents via a sidebar and analyze selected text on web pages.