FAQ

General

What is qRaptor?

qRaptor is the Enterprise AI Systems Platform — it lets you build, deploy, and manage complete business applications and AI agents under one governance layer. An AI system here means the whole system: applications, APIs, transactional data, workflows, agents, identity, permissions and governance. See What is qRaptor? for a full introduction.

Can qRaptor build a complete business application, or only AI agents?

A complete application. qRaptor generates full-stack web and mobile apps backed by a relational PostgreSQL database, with a REST API, authentication, roles and page-level permissions, business rules, workflows and a full UI — the kind of system a team runs its operations on. See Apps.

What kind of business systems can I build?

Complete business systems, not just assistants around one: CRM, order management, service management, inventory and procurement; customer, distributor and partner portals, storefronts, booking and field apps; case management, approvals and back-office consoles; AI agents and copilots; voice applications on a real phone number; and workflow automation across multiple systems. Each one is a full-stack application with its own relational data model, APIs, roles and permissions, with agents inside it where they earn their place. See Apps for how generation works.

Can qRaptor modernize an application we already have?

Yes, by using the existing system as evidence rather than as a foundation. qRaptor indexes the existing codebase and recovers its data model, API surface, business rules and integration points; those become the input to a new application on a current architecture. This is understanding rather than automated conversion. See Context Graph.

Can qRaptor run applications without AI agents?

Yes. AI agents are optional components of an application, not a prerequisite. An app with no agents at all is a normal thing to build in qRaptor.

Is my application data stored in a graph database?

No. Generated applications use a relational PostgreSQL database, and you can browse the tables and their ER diagram in the Data Vault. The App Context Graph is a build-time model of your application’s structure — pages, components, APIs, data models, business rules and access policies — used to generate and modify the app coherently. Your business data does not live in it.

Does qRaptor only add AI to systems I already run?

No. qRaptor works in three modes: build a new business system, modernize an existing one, or extend systems you already operate with governed agents and automation. Most real deployments combine them — a qRaptor-built application alongside integrations into existing systems of record.

Do I have to build the governance and security myself?

No. Access rules, tool permissions, approvals, data rules and audit are enforced by the platform beneath the model, for humans and agents alike — not assembled per project and not written into prompts. See Platform governance.

What can qRaptor connect to?

Configurable integrations for Salesforce, HubSpot, ServiceNow, Jira, Slack, Microsoft Teams, GitHub, Azure DevOps, cloud storage, email and more; databases including PostgreSQL, MySQL, SQL Server, MongoDB and Elasticsearch; any MCP server; and anything with an HTTP API as a custom tool. Systems behind your firewall are reached through qRemoteX without inbound exposure. See Integrations for the full picture.

Who owns the application qRaptor generates?

You do. The application, its agents, data model and policies can be exported and run on infrastructure you control — see Export as an appliance.

What’s the difference between an AI Agent and a Task Agent?

• AI Agent — Config-driven, uses LLM planning to dynamically select tools and respond. Best for conversational assistants.
• Task Agent — Graph-based visual workflow with explicit control flow (conditions, loops, parallel execution). Best for deterministic, step-by-step processes.

Do I need to know how to code?

No. The visual Agent Builder lets you create workflows without writing code. However, the Code node is available for advanced users who want to run custom Python logic.

Accounts & billing

Is there a free plan?

Yes. The Free plan includes 1 project, 3 agents, 75 monthly credits, and community support. No credit card required.

How do credits work?

Credits are consumed when your agents use LLM calls, tools, and data operations.

Can I change my plan at any time?

Yes. Upgrades take effect immediately. Downgrades take effect at the end of the billing period.

Agents & building

How many agents can I create?

It depends on your plan — from 3 (Free) to unlimited (Enterprise).

Can agents call other agents?

Yes. Use the Agent Call node in a Task Agent, or enable the A2A protocol on an AI Agent to expose it as a callable service.

For external systems, qRaptor’s A2A support is standards-compliant JSON-RPC 2.0 (A2A 0.2.x and 0.3.0, via message/send), so agent frameworks such as Google ADK and LangGraph, and A2A-capable enterprise platforms, can invoke a deployed agent directly. See A2A integration.

What LLM models are supported?

qRaptor supports multiple LLM providers. Available models depend on your plan. Configure models in Configuration → LLM Settings within your project.

Can I bring my own LLM API key?

Enterprise plans support custom model endpoints. Contact sales for details.

Deployments

What’s the difference between preview and production deployments?

Preview is a temporary environment you use while building, inside the app, copilot, or agent editor. Production deployments are always-on, serve real users, and support custom domains. See the Deployments overview for the full comparison, and Production deployments.

Can I use my own domain?

Yes, on Starter and above. See Custom domains.

How do I authenticate API calls to my deployment?

Use API keys (for server-to-server) or OIDC (for end-user authentication). Both are configured in deployment settings.

Data & security

Where is my data stored?

On the managed cloud, data is stored in secure cloud infrastructure, and Enterprise plans offer data residency options. If data cannot leave your network at all, you have two further options: run execution inside your own environment with qRemoteX, or take the whole system with you as an exported appliance.

Is my data used to train models?

No. Your data is never used to train or fine-tune any LLM models.

What certifications does qRaptor hold?

qRaptor is ISO/IEC 27001:2022 certified (certificate no. 26RN07JU, issued by RICL, UAF-accredited), and a third-party penetration test (VAPT) has been completed. The SOC 2 Type II observation period is underway. HIPAA and GDPR policy templates are available for Enterprise plans — contact sales for the current evidence pack.

Still have questions?

Reach out to us — see the Support page for contact options.