What is the Data Agent feature and who should be using it?
The Data Agent is an AI-powered agent within the Hoop platform designed to research and answer custom business questions. It works by analyzing your internal data, including your CRM, customer conversations, and documents, alongside approved web sources.
This feature is ideal for operations, sales, and CRM teams who need rapid, accurate, and context-aware insights without manual data aggregation. Instead of relying on generic models, the Data Agent provides automated insights grounded in your specific company context, making data analysis scalable and actionable across Hoop.
How does the Data Agent process my company's data and provide answers?
The Data Agent operates by analyzing your company context at scale, pulling information directly from integrated sources like records, calls, emails, files, and approved external sources. It does not just return a summary; it writes back its findings directly into Hoop.
The results manifest as smarter building blocks that enrich your data:
- Smart Properties: AI-derived answers that populate fields per record.
- Smart Actions: Workflow steps used to research, categorize, and transform data automatically.
- Smart Columns: AI-generated columns in Data Studio that enrich your datasets for better analysis.
This deep integration ensures that insights are not isolated but immediately actionable within your existing workflows on the Hoop platform.
What is the typical setup process and time to value for the Data Agent?
Setup for the Data Agent is streamlined within the Hoop platform settings. Initial configuration primarily involves defining the data sources it can access, such as connecting your CRM, email, and document repositories. You also set the custom questions and prompts you want the agent to focus on.
The time to value is nearly instantaneous once the connections are established, especially if your data is already within Hoop. Since the agent works with your existing data structures and writes results back into properties and columns, teams can start asking questions and seeing automated insights within a few hours, accelerating decision-making and removing manual lift from the start.
Which pricing plans include access to the Data Agent functionality?
The Data Agent is available across multiple Hoop pricing tiers to accommodate businesses of various sizes and complexity. You can access this powerful AI feature if your organization is on the core, pro, or enterprise plans.
Each plan typically includes varying levels of usage limits, such as the volume of queries, number of smart properties, or the complexity of the automated actions you can deploy. Organizations on the enterprise plan usually benefit from the highest usage limits and premium governance features, ensuring the Data Agent scales seamlessly with the business's growing operational needs on the Hoop platform.
What security and governance measures are in place for the Data Agent?
Hoop prioritizes governance and transparency for the Data Agent. Access controls and approvals are set by administrators, ensuring only authorized teams can view or utilize the agent's outputs. All agent activity is logged so teams maintain visibility into what the agent did and why, fostering trust and accountability.
The system is designed to keep humans in control while automating data lift. It adheres to standard data privacy protocols by only processing information from approved sources—your internal records and verified web sources. This structure prevents the agent from accessing or sharing sensitive data inappropriately.
How can teams ensure the Data Agent continually improves over time?
The Data Agent is designed with built-in mechanisms for continuous improvement, ensuring its outputs remain relevant and accurate as your business evolves. Improvement is driven by direct user interaction and system monitoring.
Key feedback loops include:
- User Feedback: Teams can provide feedback on specific outputs to refine the prompts and resulting answers.
- Exclusion Rules: Administrators can set rules to filter out non-actionable or irrelevant events and data points.
- Quality Dashboards: Stakeholders have access to quality metrics and performance dashboards to track accuracy and impact.
This iterative process allows the Data Agent to become smarter and more aligned with your specific business objectives over time, maximizing its value within Hoop.