Platform Overview

This page gives you a bird’s-eye view of what powers qRaptor. You don’t need to understand this to use the platform — but it helps you appreciate the capabilities at your disposal.

qRaptor is one platform for the whole lifecycle: you build apps and agents, they run and do the work, they connect to your data and systems, and you deploy them anywhere — all governed by design, with humans in control.

Every stage runs under one governance layer — RBAC, human-in-the-loop approvals, audit, and observability (see Governed by design below).

Build

Turn an idea into a working app or agent.

• Vibe Code — Describe what you need in natural language and qRaptor generates a production-ready full-stack app. It’s powered by the App Context Graph (a structured representation of your app’s entities, relationships, and files), self-correcting (if a build fails, it diagnoses and fixes the issue), and iterative (describe a change and it updates the app).
• Visual agent builder — Design agents on a drag-and-drop canvas, connecting LLMs, tools, data, and approval gates.

Run

Three building blocks do the work — an App your people use, AI Agents that do the work, and Task Agents that run automatically:

• AI Agents run conversationally: they reason, plan, call tools, and draw on memory to respond in natural language.
• Task Agents run a workflow graph node-by-node for deterministic, repeatable processes.

The runtime handles this for you: session management (conversation state across messages), three-tier memory — Profile (user preferences), Episodic (session history), and Semantic (learned knowledge) — and tool execution across HTTP tools, Python (local or remote), and MCP.

Connect

Agents work across the systems you already run, not around them.

• Data Vault — Secure storage for tables, documents, vector stores (RAG), and agent memory.
• Tools — 40+ built-in tools plus your own custom HTTP tools.
• MCP (Model Context Protocol) — Connect to any MCP server to give your agents access to external tools and data.
• qRemoteX — Run scripts, call internal APIs, and execute agents inside your own environment (on-premise, VPC, or GPU) without exposing your systems.
• External APIs — Connect to any REST API via custom HTTP tools; A2A (Agent2Agent) exposes your agents as standards-compliant JSON-RPC services that other agents and platforms can call.

Deploy

Ship to production and reach users wherever they are — a web chat widget, voice and telephony, messaging channels, or a programmatic API — on demand, on a schedule, or triggered by events. Preview environments let you test safely first, and production deployments support custom domains. See Deployments for the full picture.

Governed by design

Governance isn’t an add-on — it wraps everything above:

• RBAC — Role-based access control over who can do what.
• Human-in-the-loop — Approval gates pause execution for human review before critical actions.
• Content & budget policies — Control what LLMs can generate, and cap spending per agent, per project, or per workspace.
• Audit & observability — Every action is logged with full traceability; real-time traces, run history, and cost tracking show you exactly what happened.

What this means for you

You focus on what your agents should do and what your apps should look like. qRaptor handles:

• Executing agent logic reliably at scale
• Managing sessions, memory, and state
• Connecting to tools, data, and external services
• Securing everything with governance and audit
• Deploying to multiple channels simultaneously

Next steps

• Glossary — Definitions of platform terms.
• Create your account — Start building.