Self-Hosted Agentic AI
Run Xyner AI on your own Kubernetes, in your own accounts, on your own schedule. This page is written for the team that would actually operate it: what you need in place, how the upgrade path works, where the hybrid alternative fits — and the honest cases where self-hosting is the wrong call.
What is self-hosted agentic AI?
Self-hosted agentic AI means your team operates the agent platform itself: Xyner AI deployed as containerized workloads on Kubernetes you run — in your cloud accounts or your data center — with your identity stack, your monitoring, your secrets management and your maintenance windows. Xyner supplies versioned releases, documentation and platform support; everything executes inside a boundary you own, up to and including fully air-gapped.
Vendors usually write this page for the buyer. This one is for the operator, because self-hosting succeeds or fails on operational reality: who patches, who sizes, who gets paged. The sections below lay out the responsibility split, the upgrade mechanics and the genuine trade-offs against the managed postures — including the hybrid model that exists specifically for teams who want the data boundary without the full operations bill.
What self-hosting actually involves
Six workstreams your platform team takes on — none exotic, all real.
Cluster & capacity
The platform runs on production Kubernetes and inherits your storage, networking and scheduling practice. Capacity follows workload volume and model choices, so sizing is a scoping exercise with your numbers — we don't hand you a one-size node count and hope.
Identity & secrets
RBAC binds to your directory and SSO; connector credentials live in your secrets management. Agent permissions become part of the access-governance regime you already audit.
Model hosting — if you choose it
Hosting private LLMs (Llama and Mistral families among the 12+ supported) adds GPU capacity management. It is optional: routing to approved external endpoints, or mixing both under data-class rules, are equally supported configurations.
Release application
Versioned releases, applied in your windows with your testing and rollback discipline. Air-gapped sites get offline packages. You control timing completely — and own the staying-current obligation that comes with that control.
Observability
Platform metrics and logs flow into the monitoring you already run; the agent audit trail persists on your storage under your retention policy. No separate console to adopt, no evidence held hostage.
Environment security
Network policy, hardening and perimeter controls stay yours; the platform layers RBAC, approval gates, action budgets and immutable audit on top. Two layers, clearly divided.
The responsibility split, written down
Day-two arguments come from ambiguity. Here is the division we put in writing during scoping.
You run: infrastructure
Cluster, storage, networking, GPU capacity if hosting models, backup and environment-level security — operated to your own standards.
You run: change windows
When releases are applied, how they are tested, how they roll back — your calendar, your change board, your call.
You run: access governance
Who may build, approve and operate agents, enforced through your directory and reviewed in your audit cycle.
Xyner provides: the platform
The agent runtime, orchestration, 250+ capabilities, connector library and governance features, shipped as versioned releases with documentation.
Xyner provides: support
Platform-layer support, installation and upgrade partnership, and engineering help when something in the stack misbehaves.
Shared: the first rollout
Scoping, installation, hardening review and the first use case are run jointly — your operators learn the platform by deploying it, not by reading about it.
Self-hosted vs. managed — the trade-offs without the brochure voice
Both columns are good choices for the right team. Costs are real in both directions.
| Dimension | Multi-tenant SaaS | Hybrid (managed control plane) | Self-hosted |
|---|---|---|---|
| Control of environment | Contractual | Data plane is yours | Total — cluster to keys |
| Data boundary | Vendor cloud | Your VPC / DC for data & execution | Yours, up to air-gapped |
| Ops load on your team | None — 99.95% SLA | Light: data-plane infra only | Full platform operations |
| Upgrade timing | Vendor cadence | Managed, scheduled with you | Entirely your windows |
| Staying current | Automatic | Mostly automatic | Your discipline — and it slips |
| Provisioning time | Days | Fast | Cluster readiness gates everything |
| Model flexibility | All 12+ families on tap | Split by policy | What you host or approve — plus full prompt privacy |
| Right when… | Speed and standard compliance suffice | Data must stay in; ops team is lean | Policy mandates operating it yourself |
The failure mode we warn against: self-hosting chosen for comfort rather than mandate, then under-resourced. If no written obligation requires it, the hybrid row is usually the better engineering decision.
The hybrid alternative: self-hosted data, managed platform
The posture built for teams that want your-boundary guarantees without owning the whole stack.
Your data plane
Agent execution, case data, documents, prompts to in-boundary models and the audit trail live in your VPC or data center. The sensitive material never crosses out — the same guarantee full self-hosting gives you.
Xyner's control plane
Platform management and orchestration run as a managed service: Xyner carries upgrades, platform health and operational load, with a 99.95% SLA. Your team's job shrinks to the data-plane infrastructure it already knows.
A two-way door
Agent definitions are portable across postures, so hybrid is not a lock-in: programs move to full self-hosting when a mandate arrives, or consolidate back when it lifts. Several teams run hybrid in one region and fully self-hosted in another — one platform, two postures.
Posture mechanics are documented at deployment & sovereignty and deployment flexibility; the full private spectrum — VPC through air-gapped — is compared on the private agentic AI platform page.
What ships in the box
Self-hosting changes who operates the platform — not what the platform can do.
Agent runtime
Goal-directed agents with planning, replanning and verification — 250+ agentic capabilities.
Multi-agent orchestration
Planner, executor and reviewer agents coordinating long workflows inside your cluster.
Model router
12+ LLM families — your hosted models, approved external endpoints, or both, governed by data class.
Connector library
1,000+ integrations running next to your systems — often the shortest network path they've ever had.
Document understanding
Contracts, forms and threads processed in-boundary — extraction with citations.
Memory & knowledge
Retrieval and persistent context built from your repositories, stored on your infrastructure.
Governance suite
RBAC, approval gates, action budgets and HITL — configuration your risk team can read.
Audit & evaluation
Immutable, replayable trails plus regression suites — run and retained where you run.
Teams that self-host, and why
The mandate → the posture → what their agents do.
Banks under outsourcing rules
Processing must stay on operated infrastructure → self-hosted on-prem → KYC, reconciliation and servicing agents with full prompt privacy.
Government platform teams
Sovereignty plus an existing k8s practice → self-hosted or sovereign cloud → case-management and citizen-service agents in national jurisdiction.
Defense & classified networks
No external connectivity permitted → air-gapped self-hosting → document and logistics agents with offline release packages.
Healthcare systems
PHI boundaries → self-hosted or hybrid, HIPAA-aligned → clinical-admin and claims agents inside hospital infrastructure.
Industrial & energy operators
OT segmentation → self-hosted near the plant network → maintenance and compliance agents where clouds can't reach.
Telecoms
Network-data sensitivity and scale → self-hosted beside BSS/OSS → service operations agents in the operator boundary.
Platform-strong enterprises
A mature internal platform org → self-hosted by preference → agentic automation operated like the rest of their estate.
Sovereignty-driven programs
Jurisdictional mandates in markets like the UAE and Saudi Arabia → self-hosted or sovereign postures per national framework.
The operating rhythm after go-live
Self-hosting is a cadence, not an event. This is the loop your team owns.
1. Install together
Joint deployment onto your cluster — identity, storage, network policy and monitoring wired in from the start.
2. Harden to your standard
Your security review against the deployed platform, with the responsibility split agreed in writing.
3. Run the first agents
Use case one configured, evaluated on history and live within the 6–12 week window.
4. Watch both layers
Infrastructure health in your observability; agent quality in per-workflow completion and escalation metrics.
5. Apply releases deliberately
Versioned upgrades in your windows — rehearse the first one early, because the muscle matters more than the feature list.
6. Re-evaluate the posture
Annually ask whether self-hosting still earns its cost — and know the hybrid door swings both ways.
Governance, wherever you host
The control set is identical in every posture — only the operator changes.
RBAC on your directory
Agent and user permissions governed through the identity stack you already audit.
Approval gates
Sensitive agent actions pause for named humans — thresholds per workflow and data class.
Action budgets
Hard caps on agent activity — bounded autonomy enforced by the platform, not by hope.
Audit on your storage
Immutable, replayable trails retained under your policy — evidence that never leaves.
Model governance
Routing rules bind data classes to permitted models — enforceable to in-boundary-only.
Residency by architecture
Data lives where your cluster lives — residency satisfied structurally, not contractually.
Certifications
SOC 2 Type II, ISO 27001, GDPR-compliant, HIPAA-aligned where relevant.
Continuous evaluation
Regression suites gate agent changes in your environment. Full control list at platform security.
A ten-step self-hosting checklist
Work through these before committing — step 1 eliminates half the self-hosting projects that shouldn't happen.
1. Verify the mandate
Find the written obligation that requires self-hosting. No document, no project — choose hybrid instead.
2. Audit your k8s practice
Production Kubernetes, secrets, observability, change management — confirm the practice exists, not just the cluster.
3. Decide the model question
Host LLMs, route externally under policy, or mix — this decision drives GPU planning and scoping.
4. Scope capacity with real numbers
Workload volumes and model choices in, honest sizing out — jointly, during technical scoping.
5. Sign the responsibility split
You-run vs. Xyner-provides, on paper, before installation. Day-two clarity is bought on day zero.
6. Install and harden jointly
Deployment, identity binding, network policy and your security review — one pass, together.
7. Ship use case one
A real workflow live within 6–12 weeks — infrastructure without a workload is a science project.
8. Rehearse an upgrade early
Apply a release in a controlled window in the first quarter — build the muscle before you need it.
9. Publish operating metrics
Platform health plus agent quality metrics, visible to the teams deciding the next use case.
10. Review the posture yearly
Mandates change and models improve — keep the hybrid and sovereign options honestly on the table.
Deciding how private to go?
The sibling pages for each flavor of this decision.
Frequently asked questions — self-hosted agentic AI
The questions platform and operations teams actually ask.
What does self-hosted agentic AI mean?
It means your team runs the Xyner AI platform — agent runtime, orchestration, connectors, governance and optionally the LLMs — on infrastructure you operate: your Kubernetes cluster, your cloud accounts or your data center. You control the environment, the upgrade windows and the data boundary; Xyner supplies the platform, releases and support.
What do we need in place to self-host?
A production Kubernetes practice is the core prerequisite: the platform deploys as containerized workloads and leans on your existing storage, networking, identity and monitoring. Exact capacity depends on workload volume and whether you host models locally, which is why sizing happens in technical scoping with your team rather than from a generic datasheet.
What skills does our operations team need?
The same ones a serious internal platform already demands: Kubernetes operations, secrets and identity management, observability, and change management for release windows. If you host LLMs, add GPU capacity management. No Xyner-proprietary operational skill set is required — that is a deliberate design choice.
How does the upgrade path work?
Releases ship as versioned packages. Your team applies them in its own maintenance windows with its own testing and rollback discipline — the platform does not force upgrades on you. Air-gapped sites receive offline transferable packages. The trade-off is honest: you gain control of timing and lose the always-current cadence a managed service provides.
Do we have to host the LLMs ourselves?
No — it is a separate decision from self-hosting the platform. You can host private models (Meta Llama and Mistral families among the 12+ supported) on your own GPU capacity, route to approved external model endpoints where policy allows, or mix both under routing rules that bind data classes to permitted models.
What is the hybrid managed-control-plane alternative?
Hybrid keeps agent execution, data and audit in a data plane inside your VPC or data center, while Xyner operates the control plane and carries the upgrade and operations load. It exists precisely for teams that want self-hosted data boundaries without the full self-hosted operations bill — and many programs that start evaluating self-hosting choose it.
When is self-hosting the wrong choice?
When nothing in your regulation or contracts requires it. If your obligations are satisfied by a dedicated VPC or hybrid deployment, self-hosting adds infrastructure cost, upgrade labor and slower provisioning for no additional compliance value. We say this plainly because mis-sold self-hosting fails as a program within a year.
What does Xyner support and what do we own?
You own infrastructure, capacity, release application and environment-level security. Xyner provides the platform, versioned releases, documentation and platform-layer support, and partners with your team during installation and upgrades. The split is written down during scoping so there is no ambiguity on day two.
Can the platform feed our existing monitoring?
Yes. Platform metrics and logs integrate with the observability stack you already run, and the immutable agent audit trail is stored on your infrastructure under your retention policy — operations and compliance both see the platform through tools they already trust.
Do self-hosted deployments get the full integration library?
Yes. All 1,000+ pre-built integrations — SAP, Oracle, Microsoft, Salesforce, ServiceNow, Workday, databases, document repositories and REST/SOAP APIs — run inside your network under scoped credentials, which often simplifies connectivity to on-prem systems.
What security certifications back the platform?
Xyner AI is SOC 2 Type II and ISO 27001 certified, GDPR-compliant and HIPAA-aligned. Self-hosted deployments layer the platform's RBAC, human-in-the-loop approvals, action budgets and audit trail on top of the controls your environment already enforces.
How long does a self-hosted rollout take?
A first production use case typically lands in 6–12 weeks, with installation and use-case configuration running in parallel: cluster deployment and hardening, optional model hosting, integration wiring, governance setup, evaluation and go-live.
Go deeper on the platform
Reference material for the evaluation.
Put self-hosting through a real scoping
Bring your platform team and your mandate. We'll size it against your actual workloads — and tell you honestly if hybrid serves you better.
Request a Xyner AI Demo Talk to Deployment Engineering