Enterprise data plane
Existing systems store, transform, process, govern, and deliver actual data. Maysano does not require enterprise data to be physically moved into its platform.
Maysano
MAYSANO · REFERENCE ARCHITECTURE
Maysano Reference Architecture
The business and data product operating layer for governed, AI-agent-first enterprises.
01 · LOGICAL REFERENCE ARCHITECTURE
A connected operating layer, not another data platform
Maysano is the central operating capability for business and data product context. The diagram shows architectural responsibilities, not a mandatory request-processing pipeline.
In enterprise deployments, Maysano connects to existing data catalogs, platforms, and governance systems. In the all-in-one offering, Maysano provides an integrated operating environment with optional metadata capabilities and local-first AI.
02 · THREE ARCHITECTURAL PLANES
Separate the data, operating, and AI execution responsibilities
Maysano operating plane
Maysano manages connected objectives, use cases, products, ownership, dependencies, lifecycle, governance, and delivery relationships.
AI execution plane
AI agents use permitted portfolio context, defined workflows, model services, operational controls, and accountable human review.
03 · KNOWLEDGE GRAPH AND OWNERSHIP
One connected operating graph. Clear system ownership.
Maysano maintains managed portfolio and business-decision context. External systems remain authoritative for the information and responsibilities they manage.
| Responsibility | Primary authority |
|---|---|
| Business objectives and use cases | Maysano-managed portfolio |
| Data product portfolio relationships | Maysano |
| Product lifecycle, versions, and decisions | Maysano-managed products |
| Asset metadata and technical lineage | Existing catalogs and metadata systems |
| Physical data storage and processing | Existing data platforms |
| Enterprise identity and access enforcement | Existing IAM and security systems |
| Enterprise policies and regulatory authority | Existing governance and compliance functions |
| Agent workflows and their activity records | Maysano |
| Engineering tickets and implementation execution | Delivery systems such as Jira |
04 · OPEN STANDARDS
Open standards at the foundation
Machine-readable definitions support portability, validation, interoperability, and agent-ready context. Product specifications describe individual products; Maysano connects them to the broader portfolio graph and operating decisions.
Supported standards, integrations, and configuration details should be verified for the target environment. This page does not assert a particular specification version or universal connector coverage.
05 · GOVERNED AI AGENT ARCHITECTURE
AI agents operate with business context and defined controls
The knowledge graph supplies contextual relationships. Standardized recipes define repeatable work; model services and tools provide permitted execution; governance controls and authorization systems determine what may happen next.
Not prompt-only control. An LLM prompt does not enforce security. Permissions, workflow design, validation, review, monitoring, and enforcement remain separate responsibilities.
Inspectable operations. Evidence and activity records make work reviewable; governed agent design improves control but does not guarantee correctness.
06 · DEPLOYMENT ARCHITECTURE
Two Deployment Models. One Maysano Operating Model.
Shared Maysano operating model
Knowledge Graph · Portfolio · Governance · AI AgentsOpen standards · Lifecycle · Decision evidenceALL-IN-ONE
Local-first hybrid AI
| Capability | All-in-one |
|---|---|
| Target | Smaller organizations, private AI environments |
| Deployment | Local-first environment |
| LLM | Apple Silicon-optimized local server |
| Model routing | Local default, optional cloud |
| Knowledge graph | Maysano |
| Portfolio and governance | Maysano |
| Existing catalogs | Optional |
| Data management | Optional add-on capabilities |
ENTERPRISE
Customer cloud
| Capability | Enterprise |
|---|---|
| Target | Larger organizations with established systems |
| Deployment | Customer cloud |
| LLM | Customer-approved models |
| Model routing | Customer-defined model infrastructure |
| Knowledge graph | Maysano |
| Portfolio and governance | Maysano |
| Existing catalogs | Integrated where available |
| Data management | Existing enterprise stack |
All-in-one is not an all-replacement claim. It provides a cohesive Maysano operating environment—knowledge graph, portfolio management, governance, agent workflows, and local AI infrastructure—without requiring an organization to assemble a complex enterprise AI stack first. It does not replace every data store or business application.
Local-first hybrid AI. The Apple Silicon-optimized LLM server supports up to 16 concurrent LLM connections and can route selected tasks to cloud models under configured criteria. Trust boundaries, data movement, and the applicable model-server configuration must be confirmed for the target environment.
07 · END-TO-END OPERATING EXAMPLE
From business discussion to governed product delivery
A product manager receives customer-retention workshop notes. Context continues across source material, agent preparation, accountable review, managed portfolio records, and configured delivery execution.
Preparing a Jira task does not mean that a product has been implemented. It prepares delivery work after the relevant decision and lifecycle steps.
08 · ARCHITECTURE BOUNDARIES
What Maysano owns. What stays in your existing stack.
Maysano owns connected business and product operating context within its managed scope. Existing systems continue to own physical data, technical metadata where applicable, enterprise security enforcement, regulatory governance authority, and engineering execution.
Metadata management can be added for organizations without an established metadata solution, but it is not the primary Maysano product.
NEXT STEP
See the architecture applied to your environment
Explore how Maysano connects your existing data platforms, business objectives, product portfolio, governance, and AI operations without replacing your current investments.