INSYTO×ZETARIS

Authorized reseller & systems integrator

Governed data access for enterprise AI.

Insyto brings architecture, integration and governance delivery to Zetaris's federated data platform. Connect distributed information to analytics and AI without requiring every source to move into one new repository first.

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Explore the architecture
01 / THE DATA PROBLEM

The data is already there. Access is fragmented.

CRM, ERP, Microsoft, operational databases and documents are rarely in one place. A new AI or analytics use case should start with source ownership, access rules and the question to answer, not an automatic copy of every dataset.

COMMON STARTING POINTCopy → pipeline → warehouse → another consumer

Useful for some workloads, but costly and slow when every new question requires another feed.

FEDERATED OPTIONSources → governed access → analytics or AI

Query appropriate sources in place. Persist, cache or move data when latency, transformation or workload design calls for it.

02 / REFERENCE ARCHITECTURE

A governed layer between sources and use.

This conceptual architecture shows where the Zetaris Data Harness fits. Insyto scopes the connections, semantics and access model for the use case; the exact deployment and data path depend on the environment.

01 / CONNECTED SOURCES
CRM / ERPMicrosoft 365SQL / APIsCloud / on-prem
DATA HARNESSZetaris

Query Director

Routes federated queries across connected engines and sources.

Semantic layer

Gives business concepts a consistent meaning across systems.

Data catalog

Makes connected assets and metadata easier to discover.

Governed access

Applies defined identity, permissions and policy boundaries.

AI connection

Exposes approved context through MCP and agent workflows.

03 / APPROVED USE
AnalyticsApplicationsAI assistantsAgents
Query-in-place is an option, not a rule for every dataset. Network boundaries, performance and governance decide where materialization belongs.
03 / DEPLOYMENT

Bring the platform into your cloud.

Zetaris describes a bring-your-own-cloud deployment model. The platform can run in the customer's cloud account, alongside existing data and security boundaries. Insyto evaluates deployment fit, access design and the integration work needed for each environment.

Customer cloud account Defined access boundaries Existing data estate
YOUR CLOUD ENVIRONMENT
Zetaris deploymentQuery servicesSemantic layerCatalog & metadataGoverned connections
Your data · your access model · your operating decisions
AI ASSISTANT / AGENT
GOVERNED SEMANTIC CONTEXT
ZETARIS / APPROVED QUERIES
ENTERPRISE SOURCES
04 / AI & AGENTS

AI needs context, not just connectivity.

A model reaching raw tables is not the same as an approved answer. Business definitions, identity, permissions and source ownership shape what an assistant should see. Zetaris presents semantic and governed access capabilities, including MCP connectivity and AgentFlow; Insyto designs the use case and its control boundaries.

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05 / INSYTO DELIVERY

The platform is one part of the work.

From source selection to an operating handoff, Insyto's role is to make the architecture useful and governable in your environment.

  1. 01

    Discover

    Map sources, ownership, use cases and governance constraints.

  2. 02

    Design

    Define federation, semantics, access boundaries and deployment fit.

  3. 03

    Implement

    Configure connections, models, integrations and approved workloads.

  4. 04

    Activate

    Connect analytics, applications or AI to governed data products.

  5. 05

    Operate

    Review access, query behavior, changes and ongoing optimization.

06 / WHERE IT FITS

Start with a real business question.

These are architecture patterns to evaluate, not pre-packaged outcomes or claims of completed Insyto projects.

01

Cross-system operations

Analyze information held across CRM, ERP, support and operational systems without beginning with a wholesale migration.

02

AI grounded in enterprise context

Give approved assistants a governed route to business definitions and permitted source data.

03

Hybrid data access

Connect cloud and on-premises systems while evaluating where replication still has a place.

04

Customer and operational views

Model shared entities and definitions across distributed systems for reporting or applications.

07 / MICROSOFT CONTEXT

Extend the Microsoft data estate where it makes sense.

Zetaris publishes an integration story for Microsoft Fabric and Power BI, including access to data outside the Microsoft stack. Insyto can assess where federated access complements Fabric analytics and where native Fabric ingestion or other patterns are the better choice.

Explore Insyto's Microsoft practice
MICROSOFT FABRIC
analytics & reporting
ZETARIS
federated access & context
INSYTO
architecture & delivery
08 / TECHNICAL ECOSYSTEM

Open architecture, selected for the workload.

Zetaris describes support for multiple engines, data formats and connection methods. Source compatibility, policy and performance need validation during design.

Microsoft AzureMicrosoft FabricSnowflakePostgreSQLS3APIsApache SparkTrinoPrestoIcebergDeltaMCP
09 / RELATED SERVICES

A route from advisory to operations.

A suitable data platform is chosen through assessment, delivered through engineering and supported through an agreed operating model.

01 / ADVISE

AI Governance & Security Consulting

Define decision rights, access boundaries and controls for approved use cases.

02 / ENGINEER

Data & AI readiness checklist

Review source ownership, integration constraints and governance before delivery.

03 / ACTIVATE

Data & AI guidance

Explore governed data and AI patterns for a defined business use case.

04 / OPERATE

Discuss an operating scope

Agree the platform responsibilities and handoff needed after implementation.

10 / EXISTING FOUNDATION

The wider Insyto data-to-AI view.

Zetaris is one enabling platform in a broader architecture that also includes identity, governance, analytics and the selected AI workload. This existing Insyto reference diagram keeps those relationships visible.

Explore Data & AI guidance
Layer

Data Sources

Microsoft 365CRMERPServiceNowSQL DatabasesCloud ApplicationsBusiness DocumentsOperational Systems
Layer

Governed Data Integration Layer

Federated Data AccessSemantic Data LayerGoverned Query Access

Enabled through platforms including Zetaris, Microsoft Fabric and approved cloud data services.

Layer

Security & Outcomes

Microsoft Entra IDMicrosoft PurviewZero TrustPower BIMicrosoft FabricPrivate AIMicrosoft CopilotAI Agents
11 / KNOWLEDGE & PROOF

Work through the questions before deployment.

These Insyto resources support readiness and governance decisions. We are not presenting vendor case studies as Insyto delivery outcomes.

Assessment guide

Data & AI Readiness Checklist

Knowledge Center

Preparing Your Data Estate for AI

Knowledge Center

AI Governance Framework

INSYTO×ZETARIS

Your data already exists.
The architecture decides how it can be used.

Talk through your sources, access constraints and first analytics or AI use case with Insyto.

Discuss your data architecture Explore Data & AI services