Deliver actionable insights fast with governed agentic workflows.
Qrvey helps SaaS teams deliver AI-native analytics directly inside their product — with conversational workflows, structured AI agents, and governed access to multi-tenant analytic environments.
Most AI analytics experiences
break the product experience.
SaaS teams are under pressure to add AI into their products — fast. But most AI solutions introduce new problems:
The challenge is no longer simply “adding AI.”
It's delivering AI experiences that operate within the structure, workflows, and governance model of your SaaS product.
Meet Qrvey's Embedded AI Analytics.
Qrvey embeds AI directly into analytics workflows so SaaS product teams can design, control, and deploy AI-driven analytics experiences inside their applications.
The platform combines three core components:
Qrvey Sidekick
A conversational AI assistant embedded directly into the analytics experience.
AI Agents
Structured AI capabilities designed around analytical tasks, workflows, and domain-specific use cases.
Qrvey MCP Server
The controlled access layer connecting AI to datasets, dashboards, metadata, and tenant-aware permissions.
Together, they provide a governed framework for embedding AI into customer-facing analytics without sacrificing control, alignment, or product consistency.
From data to answers to action — inside your product.
Sidekick operates directly inside your analytics experience, providing a conversational interface that feels native to your application.
Use prebuilt agents for common analytical workflows or define custom agents tailored to your product and customer use cases.
The Qrvey MCP Server securely connects agents to datasets, dashboards, metadata, and tenant-specific permissions.
AI-generated outputs remain aligned with how analytics is defined, secured, and delivered across your SaaS platform.
Built for real analytics workflows.
Conversational analytics with Qrvey Sidekick.
Sidekick gives users a conversational interface for exploring data, generating insights, and interacting with analytics directly inside your product.
Unlike generic AI chat interfaces, Sidekick operates within your application's workflows, terminology, and analytics environment.
- Embedded conversational analytics experiences
- Guided workflows from exploration to insight
- Product-controlled placement and behavior
- Context-aware responses aligned to your application
Customers get answers faster without leaving your application, increasing product engagement while reducing reliance on support teams and static dashboards.
Structured AI Agents.
AI capabilities are delivered through agents that represent defined analytical functions with controlled access to data and actions.
Teams can deploy built-in agents for analysis and visualization or create custom agents designed around product-specific workflows.
- Built-in analytical agents
- Custom agent frameworks
- Controlled data access and actions
- Product, customer, and domain-specific contextual grounding
- Expandable AI capabilities over time
Product teams can introduce AI capabilities with confidence, delivering useful analytics experiences while maintaining control over data access, behavior, and governance.
Custom AI Agents.
Define AI experiences around your product instead of forcing your product around generic AI tools.
Custom agents can be configured with domain-specific logic, terminology, priorities, and workflows that reflect how your customers actually use your platform.
- Workflow-specific AI behavior
- Business logic alignment
- Tenant-aware contextualization
- Domain-specific AI responses
- Extensible AI architecture
SaaS companies deliver differentiated AI experiences tailored to their industry, workflows, and customer needs — creating greater product value, adoption, and retention.
Governed AI through the MCP Server.
The Qrvey MCP Server connects AI directly to the analytics environment — including datasets, dashboards, metadata, and tenant-aware permissions.
This ensures AI-generated outputs remain aligned with how analytics is structured and governed across the platform.
- Controlled access to analytics assets
- Tenant-aware permissions enforcement
- Alignment with existing analytics models
- Secure interaction with dashboards and datasets
- Consistent AI behavior across environments
AI operates within the same security, permissions, and data governance framework as the rest of your analytics platform, enabling trusted insights at scale without introducing new governance risks.
Designed for SaaS product teams
— not generic AI demos.
Qrvey gives SaaS teams a structured way to operationalize AI inside analytics workflows — while maintaining the governance, consistency, and product alignment required in customer-facing SaaS applications.
Built for teams delivering
customer-facing SaaS products.
Design AI experiences aligned to your workflows, customer journeys, and analytics strategy.
Avoid building and maintaining complex AI orchestration and analytics infrastructure internally.
Keep AI aligned with existing datasets, permissions, and analytical structures.
Deliver differentiated AI experiences that strengthen product value and retention.
Built to scale for multi-tenant SaaS environments.
Designed specifically for SaaS environments, Qrvey embeds AI into analytics workflows while maintaining the security, governance, and scalability requirements of enterprise SaaS applications.
Frequently
Asked
Questions
Embed AI into your customer-facing analytics experience
— without losing control.
See how SaaS teams are embedding AI-powered analytics that increase product value, deepen customer engagement, and drive retention.
Runs in your cloud · Tenant-aware by default