THE PRIVATE
AGENT RUNTIME
A durable, stateful execution environment for complex multi-agent workflows across cloud and on-premise environments.
The Boardroom Emergency: Agent Memory is a Liability
If your AI remembers a customer, that memory is a data asset. If you use US SaaS for agent memory, you violate GDPR and leak proprietary IP. We drop an immutable LangGraph engine directly onto your raw compute, keeping your data strictly within your private boundary.
Data Privacy & Control
All infrastructure runs inside your own environment, dedicated compute, or On-Premise setup. Your data stays under your control.
Cost Savings
vs. Managed US SaaS by running the exact same workloads on your own raw compute.
DevOps Headcount Required
We are your infrastructure department. You focus on your product.
What is a Private Agent Runtime?
It is a fully managed, stateful execution environment for complex multi-agent workflows, deployed directly inside your own cloud account, dedicated infrastructure, or On-Premise environment. We provide the durable engines required for agents to maintain long-term memory, without ever sending your proprietary data or customer interactions to third-party US-based SaaS platforms. This gives you strict data control and full ownership of your AI infrastructure.
Why deploy LangGraph inside your own environment?
Stateful AI agents require continuous read/write access to memory to function. If you rely on external SaaS providers for agent memory, every interaction, prompt, and retrieved document leaves your network perimeter. This is a massive GDPR liability and a critical security risk for enterprise IP.
By deploying natively on your AWS, GCP, Azure instances, or via secure hybrid bridge to European bare-metal GPUs (like Hetzner or Verda), you achieve zero-latency execution. Your data never traverses the public internet. We manage the underlying infrastructure—ensuring the engine is online, secure, updated, and performant—while you retain complete ownership of the data plane.
The Black Box Architecture
We deploy standardized, immutable containerized stacks. There are no snowflake configurations. Our appliances dial out to our central management plane via Tailscale, requiring zero inbound firewall ports. This allows us to monitor and self-heal your engine without compromising your network perimeter or accessing your data.
| Feature | US SaaS Agent Memory | Private Agent Runtime (BYOC) |
|---|---|---|
| Data Sovereignty | Data leaves your network (US Cloud Act risk) | 100% contained inside your own infrastructure boundary |
| Latency | High (Cross-internet API calls) | Zero (Co-located with your application) |
| Cost Structure | Variable, scales with usage and memory size | Flat monthly retainer + your raw compute |
| Infrastructure Management | Managed by vendor (Black box) | Managed by DevOps Squad on your hardware |
Core Capabilities of the Private Agent Runtime
1. Bulletproof Reliability (Durable Execution)
Build agents that persist through failures and can run for extended periods. Our Private Agent Runtime automatically saves state checkpoints to dedicated Postgres instances inside your environment. If a node fails or a container restarts, your agent resumes exactly where it left off without losing context or requiring costly API re-calls.
2. Human-in-the-Loop Oversight
Critical enterprise workflows require human supervision. Our runtime allows you to seamlessly incorporate human oversight by pausing agent execution at defined checkpoints. Inspect, modify, or approve the agent’s state before it executes sensitive actions—all while keeping the data securely within your European bare-metal or private cloud boundary.
3. Total Data Sovereignty (Stateful Memory)
Stateful AI agents remember everything. We provide the robust infrastructure needed for both short-term working memory (for ongoing reasoning) and long-term persistent memory across sessions. By hosting this memory internally, you completely eliminate the GDPR liabilities associated with sending conversational history to US-based SaaS providers.
4. Complex Workflows, Simplified (Graph Control)
Move beyond simple linear chains. The Private Agent Runtime models complex workflows as directed graphs, supporting cyclic loops, conditional branching, and multi-agent architectures. Whether you are routing intents, running map-reduce jobs, or orchestrating a swarm of specialized sub-agents, our infrastructure provides the low-level control required for reliable execution.
5. Total Visibility, Zero Data Leaks (Private Observability)
Debugging autonomous agents is notoriously difficult. We integrate open-source AI tracing tools directly into your cluster. Gain deep visibility into agent trajectories, token usage, and latency bottlenecks without paying Datadog ingestion taxes or leaking proprietary prompts to third-party monitoring platforms.
Who is the Private Agent Runtime for?
This solution is engineered for advanced SME and Enterprise engineering teams deploying autonomous agents that need stateful, long-term memory. If your AI workflows handle sensitive customer data, proprietary financial models, or internal IP, the Private Agent Runtime ensures you can scale your AI capabilities without compromising your security posture.
For teams requiring high-throughput model serving alongside their agents, we recommend pairing this with our Private AI Inference endpoints, or exploring our Dedicated Kubernetes Platform for a complete bare-metal Kubernetes cluster experience.
How Much Does The Private Agent Runtime Cost?
Plus starting at €3,000 Setup Fee
- Stateful execution environment powered by LangGraph.
- Dedicated Postgres checkpoints for short-term and long-term agent memory.
- Zero-latency execution co-located with your application in your own cloud account, dedicated infrastructure, or On-Premise environment.
- Strict data control with zero data leaving your perimeter.
- Secure Tailscale Control Plane requiring zero inbound firewall ports.
- Automated Self-Healing & Updates via immutable Helm deployments.
- 24/7 Infrastructure Monitoring with business-hours platform management SLA.
- BYOC (Bring Your Own Cloud) support for AWS, GCP, Azure, Hetzner, or Verda.
Frequently Asked Questions
What is a Private Agent Runtime?
A Private Agent Runtime is a fully managed, stateful execution environment for multi-agent workflows, deployed securely inside your own infrastructure boundary. It provides the durable Kubernetes workers and Postgres checkpoints required for agents to maintain long-term memory, without ever sending your proprietary data to US-based SaaS platforms.
Why can’t I just use LangSmith or LangGraph Cloud?
Using US-based SaaS for agent memory is a massive GDPR liability. Every interaction, prompt, and retrieved document leaves your network perimeter. We deploy the LangGraph runtime natively on your own compute (AWS, GCP, Azure, Hetzner, or Verda), ensuring 100% data sovereignty and zero cross-internet latency.
How do you manage the infrastructure inside our environment?
We deploy immutable containerized stacks via Helm and manage them through a secure Tailscale reverse tunnel. This requires zero inbound firewall ports. We monitor, update, and self-heal your engine asynchronously without ever compromising your network perimeter or accessing your application data plane.
Where is the agent’s memory actually stored?
Agent memory is stored in dedicated, highly available Postgres databases deployed directly alongside your compute workers. This ensures that short-term working memory and long-term persistent memory never leave your environment, providing strict compliance and zero-latency read/writes for your AI workflows.
What happens if an agent crashes mid-task?
Our runtime guarantees durable execution. Because the state is continuously checkpointed to your local Postgres instance, if a node fails or a container restarts, your agent resumes exactly where it left off. You never lose context or waste money on redundant LLM API calls.
Does the Private Agent Runtime support multi-agent swarms?
Yes. The underlying LangGraph architecture models workflows as directed graphs. This natively supports cyclic loops, conditional branching, and complex multi-agent swarms. Whether you are routing intents or running map-reduce jobs, our infrastructure provides the low-level control required for reliable execution.
Do we need to hire a Kubernetes engineer to maintain this?
No. We are your platform engineering team. We guarantee the infrastructure engine is online, secure, updated, and performant via automated self-healing. You get the developer experience of a managed Kubernetes cluster, but you own the underlying compute, requiring zero internal DevOps headcount.
Can we host this on European bare metal like Hetzner or Verda?
Absolutely. This is our core “Bring Your Own Cloud” (BYOC) philosophy. We can build a secure hybrid bridge to European bare-metal GPUs, giving you 70% cost savings over AWS without your data ever traversing the public internet.
How is the pricing structured compared to US SaaS?
You pay a flat monthly retainer for our management, plus the raw cost of your compute. There are no variable taxes based on memory size, number of messages, or agent execution time. You cap your AI infrastructure costs while scaling your workloads infinitely.
How do we monitor the agents without Datadog?
We deploy a fully managed, unified observability and AI tracing stack (SigNoz, VictoriaMetrics, and Langfuse) directly on your compute. You gain deep visibility into agent trajectories, token usage, and latency bottlenecks without paying Datadog ingestion taxes or leaking proprietary prompts.
Reclaim your proprietary data. Deploy Private AI.
Stop sending your proprietary IP to external APIs and managed SaaS. We deploy high-throughput inference and stateful agents directly onto your own Bare-Metal or VPC infrastructure. Execute AI workloads with zero API taxes, zero hyperscaler lock-in, and absolute control over your data.
What other AI infrastructure products do we offer?
discovery Zoom. We’ll review your AI workloads, data flows, and current cloud setup, then give you a clear Go / No-Go recommendation. If private inference, agent runtimes, or managed data services make sense for your architecture, we’ll show you the next step. If not, we’ll tell you directly.
Interested? Contact us.
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