Isolated execution
Disposable VMs or worker containers keep agent runs bounded and inspectable.
Evander™ private beta now open
Frontier AI automation, engineered for real work.
Quinth builds secure agent systems that can inspect, change, test, and ship software inside environments you control, while your secrets, approvals, and production boundaries stay under your authority.
Flagship product
Evander™ is the operating layer for AI agents that do the work.
It runs autonomous agents in isolated execution environments, routes model and package access through host-owned relays, and gives operators the control surface needed to approve, audit, resume, and recover real software work. Evander can be deployed into your cloud environment or onto your own hardware when data locality is non-negotiable.
Host-held authority
Secrets, model credentials, Git access, and package access stay on trusted host surfaces.
Human approval paths
Irreversible actions can be gated by exact-payload approvals and operator review.
Runs where your work already lives.
Deploy Evander in your own cloud, private network, or on hardware you operate. The control plane can sit inside the same boundary as your repositories, tooling, and operational data.
Hosted, managed, or local LLMs.
Use frontier model APIs, managed provider endpoints, OpenAI-compatible gateways, or locally hosted models depending on policy, cost, latency, and data sensitivity.
Keep sensitive work entirely local.
For teams with strict boundaries, Evander can operate with local model providers so source code, prompts, logs, and artifacts do not need to leave your environment.
Evander™ by Quinth
Turn frontier models into accountable execution.
Evander gives AI agents the machinery they need to work on real repositories and business workflows: controlled environments, durable state, approval gates, provider integrations, and a clear operator interface.
Platform shape
Built for teams that need AI to touch systems, not just text.
Disposable agent environments
Session manifests, isolated execution, and recovery paths for long-running work.
Narrow host-owned access
Model, package, Git, HTTP target, and MCP access pass through explicit surfaces.
Operator oversight
Approvals, audit records, workflow reports, cost visibility, and resumable sessions.
Your environment, your model boundary
Cloud, private network, or own hardware deployments with support for local model endpoints.
How Quinth engages
Quinth turns high-value bottlenecks into agent-run workflows.
The work starts with a bottleneck worth automating: reviews, deployment follow-up, support operations, integration maintenance, release evidence, or internal developer workflows. Then we design the agent boundary, connect tools, measure outcomes, and keep the system maintainable.
Agent workflow design
Tool and system integration
Runtime safety model
Operational rollout
Quinth services
Platform plus engineering judgment.
Quinth designs the automation target, integrates it into existing tools, and hardens the runtime so autonomy can scale without turning into an uncontrolled side channel.
- AI automation architecture
- Custom agent workflows and integrations
- Cloud, private network, and own-hardware Evander deployments
- Hosted, managed, and locally hosted LLM provider integration
- Secure rollout for engineering and operations teams
- Continuous measurement and refinement
Private beta