Local control
Keep data, identities, policies, and operational evidence within an agreed boundary.
Philippines-first sovereign AI
AI that stays within your operating boundary.
Saligan AI Systems gives public institutions and enterprises a practical path from AI infrastructure to governed agents in production — with customer-controlled data, policy, and operations.
Designed for
Public sectorRegulated enterpriseDigital services
Sovereignty is operational.
We build the proof.
We build the proof.
01 The operating problem
Compute is only the beginning.
Today’s AI programmes need more than a server, a model, or a proof of concept. They need an operating environment that can locate data, constrain agent actions, prove compliance, and keep running when the workload matters.
“One accountable partner from GPU rack to governed agent in production.”
Saligan brings infrastructure, control-plane software, integration, governance, and managed operations into one practical delivery model.
Open by design
Use the right hardware and models without being locked to a single infrastructure path.
Built for proof
Make policy, audit, human approval, and measurable performance part of the system.
A consequential window
The Philippines is building the conditions to become an AI services and compute hub.
PAIIM 2026–2033 connects AI compute, connectivity, power, talent, governance, and demand creation. For institutions and operators, that creates a practical opportunity: build trusted services on infrastructure designed to stay local, resilient, and useful.
Planning figures shown are drawn from the Philippines AI+ Infrastructure Masterplan and represent policy and investment direction, not guaranteed market demand or government endorsement.
AI data-center capacity proposed in the national masterplan
Across compute, power, connectivity, workforce, and adoption
Initial planning estimate for inference GPUs
Source: Philippines AI+ Infrastructure Masterplan 2026–2033
02 The Saligan stack
A sovereign AI stack that connects the physical layer to the decision layer.
Deploy as an on-premise system, inside a trusted local facility, or through an infrastructure partner. Keep the same operating controls across every environment.
AI infrastructure
Validated NVIDIA and AMD clusters, storage, network, cooling, backup, and lifecycle operations.
Saligan StackPrivate agentic AI operating layer
Model gateway, private inference, RAG, agent runtime, connectors, identity, and workflow orchestration.
Saligan OSSovereign cloud and capacity management
Tenant isolation, reserved capacity, service catalogues, quotas, cost allocation, and multi-site operations.
Saligan CloudData, governance, and resilience fabric
Policy enforcement, lineage, evaluation, human approval, audit, security, energy and cooling telemetry.
Saligan Guard03 Governed agent lifecycle
Every agent should be able to explain where it came from, what it can do, and who is accountable.
Saligan makes the full chain visible — from a customer-owned source system to a production action.
Customer data
Classify, connect, and apply residency and retention policies.
Approved models
Route work to the model and compute environment that fit the task.
Constrained agents
Give agents defined tools, permissions, sources, and approval gates.
Auditable outcomes
Observe performance, review exceptions, and keep the operational record.
04 Where we start
High-consequence workflows. Clear operating boundaries.
Government + LGUs
Services that remain accountable to citizens.
Knowledge assistants, permit and licensing flows, records support, policy research, and disaster coordination — integrated around existing government platforms.
Design an agency AI node →Regulated institutions
AI that respects the control environment.
Private knowledge agents, investigation support, compliance review, fraud operations, and policy-grounded workflow assistance.
Secure a regulated workload →IT-BPM + shared services
Human-led service, AI-enabled scale.
Quality assurance, controlled knowledge retrieval, document operations, agent assistance, and escalation workflows that preserve human judgement.
Build an inference-ready service model →Southeast Asian enterprise
Regional capacity without a one-size-fits-all operating model.
Private operations AI for logistics, manufacturing, utilities, retail, and cross-border shared services, delivered through local partners.
Plan a regional deployment →Philippines to Southeast Asia
Build the reference where the demand is real. Expand where the operating model travels.
We start in the Philippines, where AI infrastructure, public-sector digitalisation, and IT-BPM transformation are converging. We then scale through partner-led deployments in Malaysia, Indonesia, Thailand, Vietnam, and Singapore — adapting to each market’s data, language, and industry context.
Philippines / beachheadMalaysia / next marketIndonesia / scaleThailand + Vietnam / specialist deploymentsSingapore / ecosystem
05 Delivery model
Design for production from day one.
Every engagement moves from a business need to an owned, governed capability — not another disconnected pilot.
Start a discovery conversation →Discover
Map the data, workflow, policies, workload, and desired outcome.
Build the foundation
Validate infrastructure, integrate identity and data, then establish the control plane.
Govern the agent
Set permissions, test evaluations, define human escalation, and create the audit record.
Operate + improve
Train teams, monitor performance, manage the platform, and expand when the evidence supports it.
06 Trust by design
Sovereignty is a set of controls, not a marketing claim.
Customers retain ownership of their data, selected models, workflows, infrastructure, controls, and operating record.
We make lineage, permissions, human review, evaluation, and operational auditability visible.
We work with global hardware and model ecosystems while reducing avoidable dependence through open architecture and local operations.
We design with power, cooling, network, site, and workload realities in view — including regional failover when needed.
Start with the operating boundary
What would your organisation do if its AI could operate with evidence?
Tell us about the workflow, the data, and the outcome that matters. We will help you identify a production-ready first move.