Hybrid Agentic AI Architecture
The deployment model regulated enterprises standardize on: Xyner operates the control plane — orchestration, upgrades, agent definitions — while models, data, execution and audit logs stay inside your VPC. Managed-service operations, private-deployment boundaries, and a line between the two you can show your auditor.
What is hybrid agentic AI?
Hybrid agentic AI splits an agent platform into two planes with different owners. The control plane, operated by Xyner, holds what the system should do: agent definitions, workflow logic, guardrail configuration, version and rollout state. The data plane, running inside your VPC, does the work: model inference, document processing, agent execution, calls into your enterprise systems, and the audit log of all of it. The split gives you a managed service where management lives, and a private deployment where data lives.
The architecture exists because the two halves of the enterprise AI problem want different owners. Platform operations — upgrades, orchestration improvements, new capabilities — benefit from a vendor doing them continuously for everyone. Data processing — prompts, records, inference, logs — benefits from staying exactly where your security controls already are. Most deployment models force you to pick one benefit; the plane split takes both.
This page explains the architecture precisely: what each plane contains, what crosses the boundary in each direction, what never crosses, and why that specific claim is the one security reviewers can verify rather than merely trust. For the broader privacy case, see the private AI platform page.
The two planes, precisely
An architecture claim is only as good as its inventory. Here is what lives where.
Control plane: definitions
Agent and workflow definitions, prompt templates, tool configurations and guardrail policies — the blueprints. Blueprints describe how to process a case; they contain no case. Versioned, so every change to what agents are allowed to do is a recorded, reviewable event.
Control plane: coordination
Rollout state, scheduling signals, environment health and fleet telemetry. This is how Xyner ships upgrades and new capabilities continuously without touching your data — the operational reason hybrid customers get the 99.95% SLA without running the platform themselves.
Data plane: inference
LLM serving happens in your VPC — privately hosted Llama or Mistral models on your GPUs, and governed egress to commercial models only where your routing policy explicitly permits it. The policy is enforced where inference runs, inside your boundary.
Data plane: execution
Agents run here: they read your documents, query your databases, and act in your ERP, CRM and ITSM systems through connectors that execute in-VPC with vaulted, scoped credentials. Tool calls originate inside your network and terminate inside it.
Data plane: memory & knowledge
Retrieval indexes, embeddings and agent memory are built and stored in your VPC. These artifacts can reconstruct source documents — which is why an architecture that exports them, even "just for search", has quietly given up the boundary.
Data plane: audit
Every step, tool call, approval and model decision is logged where it happened — in your VPC, in your retention regime, available to your auditors without a vendor request. See audit & observability.
What crosses the boundary — and what never does
The whole architecture reduces to this ledger. It is short on purpose.
Crosses in: definitions
New and updated agent definitions, prompt templates and tool configs, versioned and signed off.
Crosses in: policy
Guardrail updates, routing rules and approval thresholds — control signals, not content.
Crosses out: health
Uptime, queue depth, error rates — operational metadata that keeps the SLA honest.
Crosses out: run status
Anonymized completion and failure counts for fleet management — no payloads, no content.
Never: prompts & outputs
What agents read and produce is created and stored in the data plane. There is no path out.
Never: records & documents
ERP rows, case files, contracts — read in-VPC, acted on in-VPC, logged in-VPC.
Never: embeddings & memory
Indexes and agent memory stay with the data they derive from — they are the data.
Never: credentials & logs
System credentials are vaulted in your VPC; audit logs live and stay under your retention rules.
Your network team can enforce this ledger with egress rules: the data plane needs a control channel and (optionally) policy-approved model endpoints — nothing else.
Why auditors and security reviewers accept hybrid
Not because the diagram is pretty — because every claim on it is independently checkable.
The claim is architectural
"Your data never leaves" is usually a contract term. In hybrid it is a network property: business data stores, inference endpoints and logs sit in a VPC whose egress your team controls. Reviewers verify it with their own tooling — no vendor attestation required for the part that matters most.
The boundary inventory is short
Two inbound flows (definitions, policy), two outbound flows (health, run status). A reviewer can enumerate and inspect all four in an afternoon. Compare that with reviewing a SaaS vendor's entire data-handling practice.
Evidence lives on your side
The audit trail is produced and retained in your environment. When a regulator asks what an agent did to a customer record, you answer from logs you hold — not from a support ticket with your vendor.
Residency falls out for free
Pin the data plane to a region and residency is satisfied by construction — inference, data and logs in-jurisdiction. Multi-region groups run one control relationship with several in-country data planes; see agentic AI data residency.
Certified on both sides of the line
Xyner AI is SOC 2 Type II and ISO 27001 certified, GDPR-compliant and HIPAA-aligned — and the data plane additionally inherits the cloud, identity and network controls your organization already audits every year.
Degraded mode is safe
If the control channel drops, the data plane keeps executing with current definitions; approvals and guardrails are enforced locally. Losing vendor connectivity pauses change, not governed work — the failure mode reviewers want.
Hybrid against the alternatives
Honest trade-offs across the three ways to run an agentic platform.
| Dimension | Public SaaS AI | Hybrid (Xyner control plane + your VPC) | Fully self-hosted / air-gapped |
|---|---|---|---|
| Business data location | Vendor environment | Your VPC, your region | Your infrastructure entirely |
| Who runs upgrades | Vendor, continuously | Xyner, continuously — 99.95% SLA | Your team, on your schedule |
| Boundary verifiability | Contractual assurances | Egress rules you inspect | Total — nothing external |
| Audit log custody | Vendor-held, exported on request | Yours, in-VPC | Yours, on-site |
| Private model hosting | Rarely | Yes — in-VPC GPUs via the router | Yes — required |
| Operational burden on you | Minimal | Low — infrastructure only | Full platform operations |
| Speed of new capabilities | Immediate | Near-immediate via control plane | Lags by your upgrade cycle |
| Fit for supervised industries | Often blocked in review | Designed to pass review | Required for air-gap mandates |
If the last row is your row, read sovereign AI platform and self-hosted agentic AI — hybrid is the middle, not the maximum.
What runs on a hybrid deployment
The same agentic workloads as any Xyner posture — with the data-plane boundary doing the compliance work.
Banking case work
Onboarding and servicing agents act on core-banking records in-VPC → supervisory expectations on data handling met architecturally → throughput rises inside the perimeter.
Insurance claims
Claims agents read policy documents and adjuster notes in the data plane → decisions prepared with citations, approvals gated → cycle time drops; files never leave.
Healthcare administration
Referral and prior-auth agents process patient data under HIPAA-aligned handling in your VPC → clinicians review prepared cases → admin load falls without disclosure risk.
Customer operations
Service agents act on CRM and billing with full context → every action logged in-plane → resolution improves within existing data commitments.
Finance & shared services
Reconciliation and invoice agents execute against ERP in-VPC → postings approval-gated, evidence retained locally → close accelerates audit-ready.
Regional subsidiaries
In-country data planes under one control plane → local residency honoured, central operations retained → one platform, many jurisdictions.
Legal & compliance review
Privileged documents processed on in-VPC private models only → routing policy enforced at inference → review scales without waiving the boundary.
IT & employee services
Access and onboarding agents act in ITSM and HR systems with scoped credentials vaulted in-plane → faster service, per-action audit.
Standing up a hybrid deployment
From VPC to production agents — the lifecycle your platform and security teams will run together.
1. Install the data plane
Deploy into your VPC with standard infrastructure tooling — your account, your region, your network segments.
2. Verify the boundary
Security reviews the egress rules against the ledger above: one control channel, optional model endpoints, nothing else.
3. Stand up the model layer
Private models onto in-VPC GPUs; routing policy written, reviewed and enforced at the router.
4. Connect enterprise systems
ERP, CRM, ITSM and databases through in-plane connectors with vaulted, scoped credentials.
5. Configure governance
RBAC, approval gates, action budgets and audit retention — enforced in the data plane, configured from the control plane.
6. Ship and operate
First use case live in 6–12 weeks; Xyner operates the platform, your team operates the boundary.
Integration inside the data plane
1,000+ connectors execute where your systems are — integration traffic never transits the control plane.
SAP & Oracle
ERP reads and writes in-plane — orders, invoices, master data, reconciliations.
Salesforce & ServiceNow
Cases, tickets and customer records — full-context agents without data export.
Workday & HR systems
Onboarding, requests and approvals on people data that stays in-plane.
Databases & warehouses
Governed queries with lineage — the warehouse never gains an external reader.
Document repositories
Contracts and case files retrieved, indexed and cited — indexes stored beside the sources.
REST & SOAP APIs
In-house and legacy systems through the governed execution layer — permissioned, logged, in-plane.
Where hybrid sits among Xyner's postures
Hybrid is one of six. Knowing its neighbours clarifies when it is the right call.
SaaS & dedicated VPC
When review requirements are lighter, Xyner-managed SaaS or a dedicated single-tenant VPC gets you running fastest — and agent definitions carry forward if you later tighten posture. See deployment options.
The regulated-enterprise default
Managed operations with an in-VPC data plane — the subject of this page. Chosen when data location and log custody are hard requirements but platform operations should not become your team's job.
On-premise, sovereign, air-gapped
When mandates exclude any external control channel, both planes move inside: on-premise Kubernetes, sovereign cloud or full air-gap. Same agents, no external connectivity at all.
Security controls across both planes
The plane split is the headline; these controls do the daily work.
RBAC on both planes
Who may change definitions, who may approve actions — scoped through role-based access control.
In-plane approvals
HITL gates enforced in the data plane — they work even with the control channel down.
Guardrails & budgets
Tool allow-lists, I/O policies and action budgets evaluated where agents execute.
Routing enforced at inference
Model policy applied in-plane — which model saw which data is a local, logged fact.
Audit in your custody
Replayable step-level logs retained under your rules, surfaced to your SIEM.
Region pinning
Data plane fixed to your jurisdiction — residency by construction, not configuration drift.
Certified platform
SOC 2 Type II, ISO 27001, GDPR-compliant, HIPAA-aligned — covering the managed side too.
Evaluated change
Every definition shipped through the control plane passes regression suites first.
The full agentic threat model — prompt injection, tool misuse, exfiltration — and the layered controls against it are on the secure agentic AI platform page.
Ten steps to hybrid in production
The path most regulated enterprises actually follow.
1. Confirm the requirement
Write down which data may not leave and who must verify that — the sentence that selects hybrid.
2. Pick region and account
Choose the VPC, region and network segments the data plane will occupy.
3. Review the boundary design
Security signs off the four-flow ledger and the egress rules that enforce it.
4. Install the data plane
Standard tooling, your infrastructure team in the driver's seat, Xyner alongside.
5. Deploy the model layer
Private models in-VPC; routing policy from your data classification, enforced at the router.
6. Integrate first systems
Only what the first use case needs — scoped credentials, in-plane connectors.
7. Configure governance
RBAC, approval thresholds, action budgets, audit retention — before testing begins.
8. Test against real cases
Evaluation suites plus process owners, on data that never had to leave to be tested.
9. Go live
First workflow in production within the 6–12 week cycle; boundary evidence archived for audit.
10. Scale on the same plane
New use cases reuse the data plane, connectors and governance — marginal cost falls each wave.
Why Xyner for hybrid
A boundary you can show, not just sign
Xyner AI's hybrid posture pairs a 99.95%-SLA managed control plane with a data plane that keeps inference, execution, memory and audit inside your VPC — backed by 250+ agentic capabilities, 1,000+ integrations and teams in New York (Global HQ), Chennai, Dubai, Riyadh, Singapore and Manama.
Frequently asked questions — hybrid agentic AI
The questions architecture and security teams ask about the plane split.
What is hybrid agentic AI?
A deployment architecture that splits an agentic AI platform into two planes: a control plane that Xyner operates — holding agent definitions, orchestration logic and platform configuration — and a data plane that runs inside your VPC, where models infer, agents execute, systems are called and data lives. You get managed-service operations with private-deployment data boundaries.
What exactly runs in the data plane?
Everything that touches business data: LLM inference (including privately hosted models), retrieval indexes and embeddings, agent memory, connector execution against your ERP, CRM and ITSM systems, document processing, and the audit log of every agent step. All of it inside your VPC, in your region.
What does the control plane hold?
Definitions and coordination, not data: agent and workflow definitions, versioning and rollout state, guardrail and policy configuration, platform health telemetry and scheduling signals. It tells the data plane what to run; it never receives what the agents read or produce.
What crosses the boundary between the planes?
Configuration and control signals going in — agent definitions, policy updates, orchestration instructions — and operational metadata coming out, such as health metrics and anonymized run status. Prompts, documents, records, model outputs and logs do not cross; they are produced and stored in your VPC.
Why do security reviewers and auditors accept this model?
Because the claim is architectural and checkable, not contractual. Reviewers can inspect the VPC's egress rules, verify that business data stores and inference endpoints have no external path, and hold the audit trail themselves. The vendor-managed part demonstrably contains no business data to lose.
How is hybrid different from a fully managed SaaS AI platform?
In SaaS, your data is processed in the vendor's environment under the vendor's controls. In hybrid, processing happens in your environment under your controls, while the vendor still handles upgrades, orchestration logic and platform operations — with a 99.95% SLA on the managed side.
How is hybrid different from fully self-hosted?
Self-hosting puts both planes in your hands: maximum control, but your team operates, patches and upgrades everything. Hybrid keeps the operational burden with Xyner while matching self-hosting where it matters most — the location of data, inference and logs. Many teams that assumed they needed on-premise land on hybrid.
Can hybrid use private LLMs as well as commercial ones?
Yes. The data plane serves models through Xyner's router across 12+ LLM families — privately hosted Llama or Mistral inside your VPC, and commercial models such as OpenAI, Anthropic Claude or Google Gemini where your routing policy permits them.
Does hybrid support data residency requirements?
Yes — the data plane is pinned to the region you choose, so data, inference and logs stay in-jurisdiction while the control plane manages deployments in any region. Multi-region enterprises run one control relationship with several in-country data planes.
What happens if the control plane is unreachable?
The data plane continues executing with its current definitions and policies; approvals and guardrails are enforced locally in the data plane. Control-plane connectivity is needed to change things — ship new agent versions or update policy — not to keep governed work running.
How long does a hybrid deployment take?
The data plane installs into your VPC with standard infrastructure tooling, and a first use case typically reaches production in 6–12 weeks — provisioning, integration through 1,000+ connectors, governance configuration and user testing included.
Is the hybrid model certified?
Xyner AI holds SOC 2 Type II and ISO 27001 certifications and is GDPR-compliant and HIPAA-aligned. In hybrid deployments your team additionally inherits its own cloud and network controls over the data plane, which is precisely why reviews tend to go faster.
Keep going
Hybrid in context — the postures beside it and the program around it.
Put the data plane where your data is
Bring your cloud architect and your security lead — we'll walk the boundary ledger together, flow by flow.
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