Agents
Specialised agents
Design, configuration and operation of agents by process, team, industry or corporate function.
Product
A complete platform for operating artificial intelligence.
Quanta goes beyond configuring agents. It provides the enterprise layer needed to turn AI into an operational, secure and reusable capability.
MCP
Predefined tools
Hundreds of options and MCP connectors to extend agent capabilities with governed access.
Workspaces
Workspaces
Separate environments by department, project, customer, region or confidentiality level.
Identity
Roles and permissions
User profiles, SSO, granular authorisation and separation of duties.
Models
Governed catalogue
Control over which models are used, who can access them and under which policies.
Governance
Audit and consumption
Activity traceability, metrics, quotas, budgets, alerts and corporate policies.
Capabilities
From the first agent to a complete enterprise platform.
AgentsWorkspacesMCPSSORBACRAGAPIsAuditQuotasBudgetsPrivate modelsObservabilityPoliciesAutomationTraceability
Functional comparison
The question is not which AI is “best”, but which operating model your organisation needs.
The table compares the standard enterprise offerings. Some capabilities depend on the selected plan, region, configuration and additional services offered by each provider.
| Dimension |
 |
 |
 |
 |
 |
|---|---|---|---|---|---|
01 Operating modelWho controls the platform and where the service is operated. |
Provider cloudManaged service operated by OpenAIInfrastructure and product evolution depend on the provider. | Provider cloudManaged service operated by AnthropicThe platform is consumed as an enterprise service. | Provider cloudGoogle-managed ecosystemDeeply integrated with Google Workspace and Google Cloud. | Provider cloudMicrosoft 365 ecosystemOperates within the Microsoft tenant and service ecosystem. | Dedicated environmentPlatform operated for the organisationDeployment, capacity and policies are designed around the customer. |
02 Private GPU infrastructureDedicated, controlled inference capacity. |
Shared service infrastructureProvider infrastructure | Shared service infrastructureProvider infrastructure | Shared service infrastructureProvider infrastructure | Shared service infrastructureProvider infrastructure | NativeDedicated GPU and distributed processingPrivate, predictable and expandable capacity. |
03 Model selectionFreedom to choose model families and sizes. |
Provider catalogueOpenAI models available under each plan | Provider catalogueClaude model family | Provider catalogueGemini models and associated services | Product-dependentModels available within the Microsoft ecosystem | Multi-modelGoverned private catalogueModels selected according to use case, cost, latency and privacy. |
04 Agents and workspacesOrganisation by teams, processes and functions. |
AvailableAgents, projects and workspaces depending on edition | AvailableEnterprise projects, capabilities and integrations | AvailableAgents and experiences integrated into Workspace | AvailableAgents within Microsoft 365 and Copilot Studio | NativeAgents, workspaces and enterprise catalogueDesigned for multiple departments, customers, regions and access levels. |
05 MCP and toolsGoverned access to external sources and actions. |
ConnectorsApps, connectors and extensibility depending on the product | MCPSupport for MCP-based connectors | Google ecosystemAgents, extensions and connectors in the Google environment | Copilot StudioMicrosoft connectors, agents and tools | MCP cataloguePrebuilt tools and dedicated serversMCP for SQL, documents, business suites, APIs and proprietary applications. |
06 Roles and permissionsSeparation of responsibilities and granular access. |
EnterpriseAdministration, SSO and access controls | EnterpriseRoles, groups and administrative controls | WorkspaceControls by users, groups and organisational units | Tenant MicrosoftPermissions inherited from Microsoft 365 | Granular designRoles by platform, workspace, agent and tool |
07 Integration with internal systemsSQL, ERP, CRM, documents, storage and APIs. |
ConnectorsCatalogue and custom development depending on edition | ConnectorsNative and custom connectors | GoogleDeep integration with the Google ecosystem | MicrosoftDeep integration with Microsoft 365 and Power Platform | OpenMCP, APIs and custom connectorsEspecially suited to heterogeneous environments and legacy systems. |
08 Data residency and isolationControl over data location and processing environment. |
Contract-dependentEnterprise controls and regional options | Contract-dependentTerms and controls of the contracted edition | Edition-dependentCapabilities vary by product and region | Service-dependentMicrosoft tenant, region and product policies | Designed around the customerPrivate environment and authorised sourcesNetwork, storage and processing are designed with the customer. |
09 Audit and observabilityTraceability across activity, consumption and operations. |
EnterpriseControls, analytics and logs depending on plan | EnterpriseAdministrative controls and available logs | WorkspaceEcosystem administration and security tools | Microsoft 365Governance and auditing integrated with the tenant | CentralisedUsage, agents, models, tools and costsTechnical and functional observability under a single governance layer. |
10 Cost modelHow consumption is planned and allocated. |
SubscriptionLicences and capabilities subject to the plan | SubscriptionLicences and limits depending on edition | SubscriptionLicences and consumption within the Google ecosystem | Licence + consumptionDependent on licences, agents and associated services | PlannableCapacity, users and consumption under a dedicated price bookLinks cost directly to infrastructure, users and usage volume. |
Native or differentiating capability
Available depending on plan
Provider-managed
Methodology note. This comparison does not assess model quality or suggest that public platforms lack enterprise controls. It summarises differences in operating approach based on publicly available information as of July 2026. Features may change and should be validated with each provider before making a contractual decision.
Where Quanta stands out
A governance layer built around your architecture.
Quanta is designed for organisations that want to decide how AI is deployed, which models it uses, which sources it can access, which actions it can perform and how costs are allocated.
01 · Control
Infrastructure and models
Private GPU capacity, a multi-model catalogue and policies aligned with technical and regulatory requirements.
02 · Integration
MCP as an operational layer
Prebuilt tools and custom development that allow agents to work with real enterprise systems.
03 · Governance
From pilot to enterprise adoption
Roles, workspaces, auditing, quotas, observability and the evolution of hundreds of agents from one shared platform.
Sources of reference
Public information used to prepare the comparison.
For production, this section can remain here or be expanded into a methodology page to reinforce transparency and avoid oversimplified comparisons.
OpenAIEnterprise data privacy, administrative controls, connectors and corporate knowledge.
AnthropicEnterprise roles, permissions, custom connectors and MCP support.
Google WorkspaceSecurity controls, Gemini Enterprise administration and Workspace integration.
MicrosoftEnterprise data protection, tenant controls, agents and Microsoft 365 Copilot.