On-Premise Agentic AI for Government
Some mandates end every cloud conversation before it starts. For those entities, Xyner AI installs the entire agentic platform — agents, orchestration, private LLMs, approval gates, audit — on Kubernetes inside the government’s own data centre. Your hardware, your network zones, your operators; agents complete the administrative work, and officials keep every decision.
What is on-premise agentic AI for government?
On-premise agentic AI for government puts the complete Xyner platform — agent runtime, orchestration, connector framework, guardrails, approval queues, audit store and, where required, the language models themselves — onto Kubernetes clusters in a government data centre. Nothing in the casework path depends on an external service: documents are parsed locally, prompts go to locally served models, and every log line lands in storage the entity owns. Agents execute administrative steps under approval gates; officials make every determination and award.
On-premise is the posture agencies choose when national data-protection and residency frameworks, classification rules or institutional policy require that both data and operations remain under direct control. It differs from a dedicated VPC in who runs the metal, and from sovereignty doctrine in its concern: this page is about architecture and operations — what gets installed, on what, and who does what on Tuesday morning.
For the surrounding control architecture — threat patterns, layered guardrails, accreditation evidence — see the cluster lead on secure agentic AI for government; for the jurisdictional argument, see sovereign AI for government.
The on-premise architecture, component by component
What actually lands on your cluster — eight building blocks, all containerized, all inside.
Agent runtime & orchestrator
Planner, executor and reviewer agents scheduled as workloads on your Kubernetes cluster.
Model serving layer
Llama, Mistral and other privately hostable families on your GPUs; routing policy pins data classes locally.
Document pipeline
Parsing, classification and extraction services running locally — uploads never leave the zone.
Knowledge & vector store
Embeddings and retrieval indexes built from your policies and case files, stored on your volumes.
Connector plane
The 1,000+ integration framework deployed beside your case, registry, ERP and records systems.
Governance services
RBAC, guardrail policies, approval queues and action budgets — enforcement runs in-cluster.
Audit & observability stack
Step logs, replay, dashboards and drift alerts, persisted to storage you control and retain.
Release & rollback tooling
Signed releases applied declaratively — pulled through a controlled channel or imported offline.
Why entities choose the on-premise posture
Five drivers that make the data centre the right answer — and one honest caveat.
Mandate, not preference
Classification rules, national residency frameworks or institutional policy simply require it. The platform treats on-premise as a first-class posture with full feature parity — not a reduced edition.
No external operator access
Day-to-day operation needs no inbound vendor connection. Your team runs the cluster; Xyner supplies runbooks, training and support. Sovereignty reviews notice the difference immediately.
Inference stays home
With models served on your GPUs, the most sensitive artifact in agentic AI — the prompt carrying case content — never crosses the data-centre boundary.
Continuity under isolation
Casework continues if external connectivity degrades or is deliberately severed. Nothing in the execution path phones home; the air-gap option is a tightening, not a redesign.
Fits the platform team you have
Standard Kubernetes, declarative manifests, an operator pattern — the same disciplines your team applies to other containerized systems, not a bespoke appliance.
The honest caveat
On-premise shifts infrastructure work to you: cluster capacity, GPU procurement, backups. Where isolation suffices without ownership, a dedicated VPC from the private spectrum may serve better — classify first, choose second.
The operations model: who does what
An on-premise platform succeeds on clear responsibilities — here is the division that works.
1. Size the environment
Xyner provides reference architectures; your team maps them to cluster capacity, storage tiers and GPU allocation.
2. Install declaratively
Manifests and an operator pattern deploy the platform into your zones; your tooling, your pipelines, your approvals.
3. Harden to your baseline
Network policies, secret-store integration, identity federation and logging wired to your data-centre standards.
4. Hand over with runbooks
Your operators take the platform with Xyner runbooks, training and support channels — no standing vendor access.
5. Operate as routine
Backups, capacity and incident response fold into existing data-centre practice; agent governance runs with the business.
6. Update on your terms
Signed releases — pulled through a controlled channel or imported offline — validated by local evaluation suites, with rollback.
What runs on it: problem → agent action → outcome
Workflows that justify a data-centre deployment — systems and approval points named.
National registry casework
Registry operations cannot depend on external services → agents validate applications, cross-check records and prepare issuance files entirely in-cluster, writing to the registry system → registrars approve every entry; the registry’s custody never leaves the building.
Benefits processing at scale
Sensitive eligibility data plus high volume → agents extract documents through the local pipeline, verify against registries, assemble files in the case system → case officers make every eligibility decision; local GPUs keep inference latency predictable at peak.
Defence-adjacent administration
Back-office paperwork in restricted zones → agents run procurement checklists, reconcile inventories in the ERP and prepare approval files inside the enclave → designated officers sign each step; the air-gap option removes the egress question entirely.
Court & tribunal support
Filings and case bundles are jurisdictionally sensitive → agents index filings, assemble hearing bundles from document repositories and track deadlines in the workflow system → registrars and clerks approve every bundle; judicial determinations remain entirely human.
Tax and customs documents
Financial filings require domestic processing → agents validate declarations, cross-check registries and flag anomalies with reasons → tax and customs officers decide every assessment; the evidence trail persists in local audit storage.
Records digitization
Archives cannot be shipped out to be understood → agents classify scans, extract metadata and file records per retention schedules into local repositories → records officers approve disposition; the archive never leaves the premises.
Inter-department workflows
Referrals between ministries sharing the data centre → agents package referrals with scoped fields, track deadlines and escalate silence across case systems → each ministry’s officers keep their own approvals; the audit shows every handover.
Payment-file preparation
Disbursements demand bounded automation → agents reconcile entitlements in the ERP and stage payment files behind a finance gate with action budgets → finance officers release every batch; the maximum possible error stays capped.
Freedom-of-information support
Disclosure searches span local repositories → agents locate responsive records, compile candidate sets with citations and flag exempt material → records officers decide every disclosure and redaction, with the search trail logged in-cluster.
In every workflow: officials and case officers make every determination, eligibility decision, enforcement action and award. Agents prepare, assemble, verify, route and execute administrative steps under approval gates — on infrastructure you own.
Integration inside the data centre
The six system families, connected without a single call leaving your zones.
Service portals & CRM
Citizen-facing channels terminating inside your DMZ — intake flows straight to in-cluster agents.
Case & workflow systems
The systems of record, often in the same halls — low-latency, role-scoped read/write.
ERP & finance
SAP, Oracle and treasury systems — reconciliation and payment staging behind finance gates.
Document repositories & records
EDRMS and archives on local storage — citation-backed retrieval, retention-aware filing.
Email & correspondence
Official mail infrastructure — inbound as untrusted data, outbound template-bound and gated.
APIs & registries
Registries and national platforms over internal REST/SOAP routes — field-scoped and logged.
Credentials live in your secret store; every connector call is authorized at runtime and logged to your audit storage. One enforcement pattern, reviewed once, applied to every integration.
Legacy on-prem automation vs. lifted cloud tools vs. on-premise agentic AI
Three ways entities have tried to automate inside the data centre.
| Dimension | Legacy on-prem RPA/BPM | Cloud tools, lifted inside | On-premise agentic AI (Xyner) |
|---|---|---|---|
| Handles case variation | No — scripts break | Partially | Reasons within policy, escalates edge cases |
| Model inference | None | Often still calls out | Local LLM serving on your GPUs |
| Architecture | Monolithic servers | Containerized, awkwardly | Kubernetes-native by design |
| Updates | Risky big-bang upgrades | Vendor-pushed | Signed releases, offline option, rollback |
| Governance | Bolted on | Cloud-account centric | RBAC, gates, budgets, audit in-cluster |
| Air-gap support | Accidental at best | Rarely viable | Native: offline licensing, updates, monitoring |
| Decision authority | Humans | Varies | Officials decide; gates enforce it |
| Evidence | Fragmented logs | Provider-held | Step-level audit on your storage |
One platform, three postures around on-premise
On-premise sits in a family — entities often run more than one posture at once.
Hybrid: managed control plane
Xyner runs the control plane while the data plane — execution, data, inference — sits in your VPC or data centre. A common first step toward full on-premise.
On-premise Kubernetes
Everything on your clusters, operated by your team, with local LLMs. The posture this page describes — full control with a managed-software upgrade path. Compared across options under platform deployment.
Air-gapped enclave
The on-premise deployment with every external path removed: offline licensing, offline updates, local monitoring. For mandates where disconnection is the requirement, not an option.
Ten steps to an on-premise go-live
Infrastructure and agent tracks run in parallel — checkpoints bind them together.
1. Select the workflow
One administrative process whose mandate justifies the data-centre posture.
2. Classify data & zones
Map data classes to network zones and storage tiers; decide if the air-gap applies.
3. Data-residency review
Checkpoint: reviewers ratify on-premise scope, model placement and log retention.
4. Prepare the cluster
Kubernetes, storage, GPUs and secret store stood up from Xyner reference architectures.
5. Install & harden
Platform deployed declaratively, wired to your identity, network policy and logging baselines.
6. Configure agents
Goals, knowledge sources, connectors, RBAC and routing policy for the chosen workflow.
7. Approval-matrix sign-off
Checkpoint: leadership signs who approves payments, determinations and notices.
8. Security accreditation
Checkpoint: in-cluster controls evidence plus certifications packaged for your accreditor.
9. Pilot on local history
Historical cases replayed in-cluster; accuracy, escalation and latency measured on your hardware.
10. Operate & extend
Go live under local monitoring; add workflows on the same cluster, governance and evidence base.
Frequently asked questions — on-premise agentic AI for government
What platform teams and accreditors ask about the data-centre posture.
What is on-premise agentic AI for government?
On-premise agentic AI for government is the full Xyner AI platform — agents, orchestration, integrations, guardrails, approval gates and audit — installed on Kubernetes inside a government data centre. Case data, prompts, embeddings, model inference and logs all remain on infrastructure the entity owns and operates, while agents execute administrative work under approval gates and officials make every determination.
What infrastructure does an on-premise deployment require?
A Kubernetes cluster on the entity’s hardware or virtualization layer, storage for databases, document processing and vector indexes, and GPU capacity if private LLMs are served locally. Xyner provides reference architectures and sizing guidance based on workflow volume and the model families selected.
Does the platform run on our existing Kubernetes distribution?
The platform is packaged for standard Kubernetes and deploys on the distributions commonly operated in government data centres. Installation uses declarative manifests and an operator pattern, so your platform team manages it with the tooling they already use for other containerized workloads.
Can LLMs run entirely on-premise too?
Yes. Xyner routes across 12+ LLM families, including Meta Llama, Mistral and other privately hostable models served on your GPUs. Routing policy can pin all workload content to local models, and in air-gapped configurations local models are the only endpoints that exist.
How do updates work without exposing the environment?
Two models: a connected on-premise deployment pulls signed releases through a controlled channel your network team approves, or a disconnected deployment imports signed offline bundles through your media process. Either way, evaluation suites run locally before updated agents return to service, and rollback is built in.
Who operates the platform day to day?
Your team, with defined responsibilities: platform operations (cluster, storage, backups) sit with your infrastructure group, agent configuration and governance with the business and AI teams, and Xyner provides support, reference runbooks and training. No external operator access is required, which matters for sovereignty reviews.
What happens if the data centre loses external connectivity?
An on-premise deployment continues operating: agents, models, connectors, approval queues and audit all run locally. External connectivity affects only optional services such as managed support channels — it is never in the execution path for casework.
Is an air-gapped installation different from on-premise?
Air-gapped is on-premise plus the removal of all external network paths. The platform supports it natively: offline licensing, offline updates, local model serving and local monitoring. Entities typically start connected on-premise and tighten to air-gapped where mandates require.
Do officials keep decision authority in an on-premise deployment?
Yes. Officials and case officers make every determination, eligibility decision, enforcement action and award in every posture. Agents prepare, verify, route and execute administrative steps under approval gates, and the on-premise audit trail records each decision and the evidence behind it.
How do agents integrate with systems inside our data centre?
Through the same 1,000+ connector framework, deployed beside your systems: case and workflow platforms, registries, ERP and finance systems, document repositories, service portals and internal REST or SOAP APIs. Credentials remain in your secret store; every call is role-scoped and logged locally.
Is on-premise still covered by Xyner’s certifications?
The platform and the organization behind it hold SOC 2 Type II and ISO 27001 certifications and maintain GDPR compliance. For on-premise deployments, these combine with your own data-centre controls, and the platform supplies the step-level audit evidence your accreditation process requires.
How long does an on-premise rollout take?
Agent configuration, integration and governance follow the standard 6-to-12-week pilot-to-production path once the environment is ready. Environment preparation — cluster, storage, GPUs, network zones — runs on your infrastructure team’s schedule, and Xyner’s reference architectures are designed to compress it.
More from the security & sovereignty cluster
The adjacent decisions around an on-premise program.
Run On-Premise Agentic AI for Government in your data centre
Bring your platform team — we will walk the reference architecture, sizing and the operations handover, then scope a pilot on your cluster.
Request a Demo Discuss Your Government Use Case