Identity and access
Manage tenant credentials and workspace access from a central control surface.
- Tenant-scoped API credentials
- Credential rotation workflows
- Workspace access boundaries
LiyaEngine for enterprise
Move enterprise AI from scattered pilots to an operating system.
Give product, platform, security, and compliance teams one governed way to define, ground, run, and observe AI capabilities without coupling every application to a model provider.
Tenant ownedDomains, knowledge, credentials, and controls remain scoped to your organization.
Policy awareGuardrails and validation travel with each callable capability.
Integration readyStable intent contracts keep provider logic out of product code.
Evidence firstTrace runtime, retrieval, policy, latency, tokens, and cost by request.
Enterprise control plane
A platform boundary every stakeholder can understand.
LiyaEngine turns AI operations into explicit resources and contracts. Teams can move quickly without asking security and platform engineering to accept an opaque stack.
Governance in the runtime
Attach guardrails, schemas, knowledge, and model policy to the capability that owns them.
- Input and output policy checks
- Validated response contracts
- Configuration separated from application code
Operational evidence
Give engineering and risk teams a shared record of how each request executed.
- Request-level traces
- Provider and model attribution
- Latency, token, and cost context
Architecture that scales
Organize capabilities by business or product domain while preserving a consistent integration edge.
- Tenant-created domains
- Reusable knowledge collections
- Agent and workflow orchestration
Enterprise deployment planning
Map environments, integrations, data controls, and rollout criteria before production traffic arrives.
- Architecture and security review
- Phased capability rollout
- Production-readiness checkpoints
Guided adoption
Work with LiyaEngine on the operating model, migration path, and first production capability.
- Technical discovery
- Implementation guidance
- Ongoing operating reviews
A deliberate path from evaluation to production.
Enterprise adoption works best when the first capability proves the operating model, not only the model output.
01
Discover
Map the use case, systems, data classes, owners, and production requirements.
02
Design
Define the domain, intent contract, knowledge boundary, and policy path.
03
Validate
Exercise realistic requests, review evidence, and complete stakeholder controls.
04
Expand
Standardize the pattern across product areas, teams, and environments.
Your AI platform should make ownership clearer as adoption grows, not create another layer only specialists can operate.
Bring one production AI requirement. Leave with an operating plan.
Talk with our enterprise team about architecture, security, migration, procurement, and the first capability your organization needs to ship.