The Openprise AI Agent capability is a platform feature that allows revenue operations teams to build, deploy, and operate AI‑powered agents directly within their data and process automation environment. It is designed to embed AI into existing RevOps workflows rather than acting as a standalone assistant or external co‑pilot. AI agents operate on governed data inside the platform, enabling tasks such as data cleansing, classification, extraction, summarization, translation, and contextual matching. The platform manages data access, model execution, orchestration, and monitoring as part of the same infrastructure used for RevOps automation. This capability focuses on operationalizing AI in a secure and compliant way. AI agents are embedded into production workflows, eliminating the need to assemble separate tools for model hosting, data preparation, security controls, and deployment. The result is AI‑driven automation that aligns with existing data governance and operational requirements.

Key Features

Embedded AI Agents

Runs AI directly inside RevOps workflows.

• AI logic integrated into data jobs and automations
• No external handoffs or disconnected tools

No‑Code AI Configuration

Builds AI‑powered processes without coding.

• Visual builders for AI‑enabled workflows
• Reusable AI components

Data‑Native AI Execution

Operates on governed platform data.

• AI uses the same data layer as automation
• Consistent rules and controls applied

Model Flexibility

Supports multiple AI model options.

• Embedded and externally hosted models
• Controlled model selection per use case

Turnkey AI Operations

Eliminates infrastructure complexity.

• Platform handles data prep and deployment
• Built‑in monitoring and governance

Security and Compliance by Design

Protects operational data.

• Data remains within the platform
• AI execution aligned with compliance requirements

Benefits

Operationalized AI for RevOps

Moves AI from experimentation to execution.

• AI embedded in real workflows
• Direct impact on operational outcomes

Reduced Implementation Complexity

Simplifies AI adoption.

• No custom pipelines or tooling
• Less reliance on IT and engineering

Improved Data Quality and Automation

Enhances core RevOps processes.

• AI‑assisted cleansing and structuring
• Smarter routing, matching, and scoring

Lower Risk and Better Governance

Supports responsible AI usage.

• Centralized controls
• Consistent compliance across workflows

Scalable AI Enablement

Supports growth and change.

• Reusable AI agents
• Flexible deployment across processes