Kubernetes ready
Scale APIs, agents, tools, and runners independently.
Deployment Choice
Operate privately or consume QACkt as a managed service.
Choose ownership and isolation based on regulatory, data residency, network, and operating-model requirements without changing the product workflow.
Privatecustomer-controlled infrastructure
ManagedQACkt-operated cloud
Dedicatedtenant option
Capabilities
A complete working system, not an isolated generator.
Air-gapped direction
Operate with private storage, models, registries, and secrets.
Private AI
Route to local models and customer-owned provider keys.
Managed operations
Use shared infrastructure with tenant isolation and managed upgrades.
Data residency
Keep source, vectors, graph context, runs, and artifacts in approved regions.
Portable services
Use containerized open-source aligned infrastructure.
Operating flow
Every stage is visible and reviewable.
Inputs, decisions, evidence, findings, approvals, and artifacts remain available throughout the workflow.
Assess
Map data, network, model, and control requirements.
Choose
Select private, managed, or dedicated tenancy.
Configure
Bind identity, secrets, storage, and observability.
Validate
Run isolation, recovery, and smoke checks.
Operate
Monitor services, queues, AI, and executions.
How it fits
Connected to the wider quality lifecycle.
This capability works with shared project context, accountable decisions, and traceable evidence from source through outcome.
01Customer edge: Identity, source systems, CI, and ticketing.
02QACkt services: Control, orchestration, agents, and tools.
03Data services: Customer-owned or managed open data plane.
01Customer edge
Identity, source systems, CI, and ticketing.
02QACkt services
Control, orchestration, agents, and tools.
03Data services
Customer-owned or managed open data plane.
04AI routes
Local, private cloud, or approved external model.
05Observability
Metrics, traces, logs, cost, and audit.
Engineering outcomes
What this changes for delivery teams.
Match deployment to regulatory constraints
Retain ownership of data and AI where required
Keep one operating model across environments
Move between deployment models without workflow redesign
Working session
Explore Deployment Choice with your own delivery context.
Bring one requirement set, workflow, or performance concern. We will map the governed path from source to executable evidence.