01 · Connect
Connect. Plug in your systems with prebuilt connectors and pipelines, with lineage from day one.
Connectors · Pipelines · Lineage
Applied AI
Agentic platform.
Connect your enterprise data, build agents on a shared understanding of your business, and run them on local or cloud AI, under one set of controls.
One governed foundation for enterprise AI. Connect the data you already have, give every agent a shared understanding of your business, and run each task on a local model inside your network or a cloud model, chosen by policy, under one set of controls.
One platform for every layer of enterprise AI.
From the systems you already run to the agents your teams use, connected and governed in one place.
Agents & applications
Operations, research, customer, and back-office agents, all built on the same foundation.
Agent Studio
A visual workspace to compose agents, tools, and approval steps.
SDK & APIs
Build on the platform from your own code and plug it into existing apps.
QD Agentic Platform
Security · Observability · Governance
Enterprise knowledge graph
Shared brain
Entities, relationships, and documents linked, so every agent works from the same context.Explore →
Agentic capabilities
Planning · Tool use · Memory · Multi-agent orchestration
The reasoning layer: agents that plan, call tools, remember, and work together.
Data connectors
Connect ERP, CRM, warehouses, documents, APIs, and sensor feeds.
Data pipelines
Batch and streaming ingestion, with quality checks and lineage.
Semantic data models
One business vocabulary over your systems, so agents query meaning, not tables.
Vector & graph memory
Retrieval over documents and relationships, with citations back to the source.
Model router
Sends each task to the right model by data sensitivity, cost, and latency.
Local AI
In your network
Open-weight models on your own hardware. The data never leaves your network.
Cloud AI
Managed APIs
Frontier models through managed APIs, for the hardest reasoning.
Agent runtime & tools
Runs agents with scoped tools, retries, and long-running workflows.
Evaluation & observability
Traces, evaluations, and cost tracking for every agent step.
Human in the loop
Approval steps wherever a decision needs a person.
DevSecOps & access control
Identity, role-based permissions, audit logs, and versioned releases.
AWS
Microsoft Azure
Google Cloud
Private cloud
On-premise & edge
Runs where your data lives
Local where it must be, cloud where it helps.
Every task goes to the right model: open-weight models inside your network for sensitive data, frontier models in the cloud when the job needs them.
Pick a task
Input
Confidential terms
Model router
Sensitivity · cost · latency
Cloud AI
Managed APIs
Local AI
In your network
Local AI. Confidential data stays on models inside your network.
From your data to agents at work.
Four steps, each building on the layer below it.
02 · Understand
Understand. Map data to a semantic model and the knowledge graph, so the platform knows what an order, asset, or customer means.
Semantic models · Knowledge graph
03 · Build
Build. Compose agents in the Studio or in code, with scoped tools and approval steps.
Agent Studio · SDK · Tools
04 · Run
Run. Run each task on local or cloud AI, and watch every step with traces and evaluations.
Model router · Observability · Evals
Governed by design.
Agents earn trust by being accountable. The same controls apply to every agent, not only the risky ones.
01
Identity & roles
Agents act with the permissions of the people and systems they serve.
02
Audit trail
Every prompt, tool call, and decision is logged and reviewable.
03
Data residency
Choose which data may reach which models, and where they run.
04
Evaluation
Agents are tested against your own cases before and after each release.
05
Cost control
Budgets and routing rules keep model spend predictable.
06
Versioned releases
Agents, prompts, and tools ship through the same review as code.
Ready to put agents on your own data?
Tell us about your systems and constraints. We’ll map the platform to them, from connectors to the models that should run each task.