| Platform approach |
A complete building and operating platform for custom AI agents: creation, knowledge, models, integrations, governance and execution are managed in one place. Extensively configurable and extensible. |
An agent platform within the Microsoft ecosystem, connected to the Power Platform and Microsoft services. |
| Internal and external use cases |
For internal business processes and for external use cases such as service and customer communication. Individual rules and action permissions govern how agents are used. Delivery across a range of channels. |
For internal and external use cases; delivery across a range of channels. [1] |
| Skills required |
Business users need no technical knowledge at all. They create, understand and maintain even multi-step AI processes in natural language. No programming or IT skills are required. |
Requires thinking in programmatic terms. For graphically modelled processes, authors need to understand the nodes, conditions and flows involved. Power Platform expertise should be budgeted for enterprise-wide operation, policies and controlled publishing. [1][3] |
| How AI Agents are built |
Agents are built in natural language; an AI assistant works out rules, edge cases and approvals in a guided interview. The result is an executable “routine” in text form that business users can read and understand. Tools and knowledge blocks are provided visually and referenced in the text. Schedules and the interplay between multiple agents can also be controlled in natural language. |
Built with AI assistance, which generates a node diagram from the input. Instructions, knowledge and tools are added via context menus; explicit process logic can be modelled using nodes and flows. [1] |
| Process description and maintenance |
The readable routine text is the automation itself and remains the working basis. Business teams adjust rules and process steps directly in the text, then test and publish changes within their permissions. There is no separate node diagram to maintain. |
Maintenance happens through the configuration of nodes and edges. For modelled processes, nodes, conditions and flows have to be adjusted. The skills required depend on how the agent is built. [1] |
| Setup and ongoing responsibility |
IT sets up access, system connections and central policies. Business owners maintain content and test cases; SCALAN consultants can support the rollout. |
The company or a partner configures environments, roles, data policies, connections and the publishing process, and keeps them up to date. [3] |
| Additional business units |
New agents use the same platform framework with their respective permissions. Business units can implement further use cases in the copilot studio alternative themselves. These are integrated into the platform via roles and departments with the corresponding approvals and rights. Policies are set centrally and apply to all business units. |
Additional teams are onboarded via roles, groups, sharing and the chosen environment structure; central policies are reusable. [3] |
| Governance and action permissions |
IT centrally defines which models, systems and individual actions are available. Action permissions can be defined comprehensively and in fine detail. Business units cannot extend these boundaries on their own. Human approvals can be built into a process. Communication with AI agents is controlled through a whitelisting procedure. |
Data policies govern connectors, knowledge sources and channels, among other things. Where it is integrated, Agent 365 adds central monitoring and policy enforcement. [2] |
| Identities and accountability |
SSO, Microsoft Entra ID and SCIM are supported. Agents belong to the organisation, and every agent has a person accountable for it. Agents themselves have an identity with a name, a role and an email address. |
Roles, teams and Entra ID groups govern access and collaboration; Agent 365 adds agent identities and ownership information. [2][3] |
| AI models |
Multiple model providers; IT centrally controls which models are approved. A suitable model can be selected per process and per AI agent. Cost tracking per provider is available. |
Multiple model providers; availability, approval status and processing terms differ. Certain external models are in preview or experimental. [4] |
| System connections |
A broad range of standard integrations, including the Microsoft ecosystem (M365, SharePoint and others). Customer-specific ERP systems and in-house developments can be connected. |
A broad connector ecosystem for Microsoft and third-party systems, plus custom extensions. [1] |
| Testing and publishing |
Reusable test cases including document processing, versioning and publishing. Controlled publishing through a multi-stage release process. Full versioning and automatic saving of drafts. |
Reusable test sets, quantitative evaluations and comparisons of test runs; controlled publishing through the corresponding lifecycle processes. [3][5] |
| Transparency and intervention |
Reasoning is fully traceable. Inputs, execution steps, decisions, tools used, results and consumption are all disclosed. Agents can be centrally paused or deactivated, and individual running executions can be stopped. |
Activity maps show inputs, decisions and outputs. Central usage controls complement the execution analysis. [2][6] |
| Data location |
The platform and the AI models are processed in Frankfurt. The processing location of connected third-party systems needs to be considered separately. Customer-hosted models can be connected. |
EU Data Boundary with the corresponding tenant and environment configuration. Data flows also depend on the features, models and connected services in use. [4][7] |
| EU AI sovereignty |
A German platform provider, processing in Germany and a choice of different model providers. European models can be part of your own AI strategy. |
European data residency is possible; the agent platform remains part of the Microsoft ecosystem. External models are available as well. [4][7] |
| Price and billing |
According to the SCALAN pricing overview, Business starts at €129 per month with 500 SCALAN credits and an unlimited number of users; usage-based billing via tiered credits.
500 SCALAN credits correspond to roughly 31,500 Copilot credits. |
€173.30 per month and pack with 25,000 Copilot credits; alternatively usage-based billing with an Azure subscription. |
| Scope of service and additional effort |
A single platform for building, governing and operating custom AI agents. Connection to a range of channels is included as standard (AI agents can be used in Microsoft Teams, Slack, WhatsApp, Telegram and email). SCALAN can support the rollout and agent development with consulting; individual services and the scope of the plan are defined in the offer. |
The agent licence includes entitlements for connectors. Additional services, licences and implementation work depend on the scenario. [3][6] |