Components of ZBrain Builder

Knowledge base

ZBrain’s knowledge base is a centralized data repository that enables AI applications and agents to access domain-specific information for accurate and context-aware responses. It supports a wide range of data formats, including documents, images, and videos. You can also import data from sources like Web URLs, Webhooks, Google Sheets, Google Slides, Google Docs, ElasticSearch, Notion, MongoDB, ServiceNow, Confluence, Jira and more. This broad data connectivity ensures flexibility and scalability, allowing your AI systems to stay informed and deliver precise, domain-relevant outputs.

App

ZBrain empowers users to create LLM-powered applications tailored to their specific needs, such as chatbots, content generation tools, customer support systems, question-answering tools, recommendation engines and more. Users can personalize the app’s features, responses, and operations, configure its settings, customize appearances, test app performance, and navigate key analytics. To ensure safe and responsible AI usage, ZBrain integrates advanced guardrails that enforce security and policy compliance. It filters harmful prompts, prevents misuse, and maintains ethical behavior across all ZBrain applications. Using ZBrain, both public and private apps can be developed and seamlessly integrated into an organization's internal workflows and customer-facing systems.

Agents

ZBrain AI agents are intelligent, purpose-built systems designed to automate and optimize business processes across diverse functions. These agents leverage generative AI to handle various tasks such as data analysis, process automation and decision support. Seamlessly integrating with diverse data sources and your organization’s existing tools and systems, ZBrain AI agents reduce deployment effort and ensure compatibility for smooth and efficient operations. You can choose from prebuilt agents designed for common use cases, build custom agents to address specific operational challenges, or assemble agent crews—collaborative teams of agents working in coordination to solve complex, multi-step tasks. When building a custom agent, the Flow component allows you to design intricate logic workflows that define the agent’s decision paths and actions without requiring extensive coding expertise.

Prompts

Prompts are structured instructions that shape how large language models (LLMs) respond to user inputs, ensuring outputs align with specific tasks, goals, or business functions. ZBrain’s Prompt Manager streamlines the creation, organization, and integration of these prompts into applications and agents built on the platform. Prompts can incorporate variables, system instructions, conditional logic, and dynamic content to enable flexible, context-aware interactions.

Equipped with version control, real-time testing, and seamless integration within ZBrain apps and agents, the Prompt Manager empowers teams to maintain consistent, high-quality AI responses. With built-in evaluation capabilities, users can test prompts against various inputs, review model responses for accuracy and relevance, and fine-tune prompts to achieve optimal output quality. It offers granular control over model behavior, enhancing the reliability, precision, and performance of language model-driven solutions across the enterprise landscape.

Monitor

The monitor functionality in ZBrain Builder provides real-time visibility and automated evaluation of AI applications and agents, ensuring consistent performance and response quality. Acting as a centralized dashboard, it captures user inputs and AI outputs, assessing them against metrics like accuracy, relevancy, success rate, and failure trends at scheduled intervals. Its intuitive interface allows teams to quickly analyze performance, spot recurring issues, troubleshoot interactions, and ensure alignment with business goals. It also features a built-in notification functionality, which enables alerts to be sent across multiple communication channels, regardless of whether a monitoring event succeeds or fails. This keeps stakeholders informed in real-time and enables swift responses to emerging issues. By automating assessments, this functionality helps maintain high-quality AI interactions, supports faster iteration, and ensures reliable, scalable AI workflows.