Rule-based automation
A predefined workflow executes known steps. Often the right choice for clear rules and stable inputs. We do not replace it with an agent without a reason.
Agentic AI needs a well-designed business process.
We have improved workflows and connected company systems for many years. Agents extend this work: interpreting information, preparing next steps and executing permitted tasks across systems. Your business process remains the starting point, not the model.
How we design agentic workflows ↓AI can carry out tasks, not just write answers.
An agent uses information, chooses next steps and invokes permitted tools. We design a business process with access rules, checks and clear boundaries. Agentic does not mean uncontrolled.
- 01
Trigger
An event or person starts a clearly scoped task.
- 02
Context
The agent reads only permitted data and knowledge sources.
- 03
Plan
It selects next steps within permitted rules.
- 04
Tools
APIs and connectors enable specific actions in CRM, ERP or business systems.
- 05
Approval
Consequential or risky actions require defined review.
- 06
Outcome
Outcomes, actions, exceptions and human fallback are recorded.
AI assistance
AI researches, summarises or prepares a decision. Your team reviews the result and executes the action.
Agentic process
Within its task, the agent can select and execute several permitted steps. Uncertainty, missing data and rule violations lead to review or fallback, not unauthorised actions.
What we define before rollout
- Task and boundaries: which actions may the agent read, prepare or execute?
- Identity and data: which person or application can access each source?
- Quality: how does the business recognise a correctly completed case?
- Failure paths: what happens with conflicting data, timeouts, duplicate execution or missing approval?
- Operations: who reviews actions, model changes, alerts and user feedback?
Agents and workflows in Copilot Studio ↗ · Microsoft Foundry ↗
Where several systems and decisions come together.
Prepare enquiries and orders
An agent classifies an enquiry, reads permitted product and customer data and checks missing details. It can prepare follow-up questions and create a CRM case. Binding prices, commitments and order approvals follow your rules.
We measure complete cases, correct assignment and permitted actions.Handle service cases using knowledge and device data
Approved documentation, previous cases and relevant device data provide context. An agent can suggest checks, add information and involve the responsible person. Missing or conflicting evidence leads to clarification, not an invented answer.
We measure supported outcomes, reopened cases and escalations.Coordinate document and approval processes
Classify content, reconcile master data and prepare the next permitted step. The agent uses defined ownership and records actions. Transactions or changes affecting customers, money or access require the defined approval.
We measure first-pass quality, exceptions and traceable approvals.In practice
What already runs today
In NXTGN AI CORE, agents search, compare and analyse and deliver reports with evidence. AI CORE is in productive use at customers. In an online retailer's customer service, AI classifies close to 1,500 tickets on a normal day and prepares replies. Through the AI CORE MCP interface, agents in Copilot Studio can also use your company knowledge without the knowledge base leaving your company.
More on NXTGN AI CORE →- AI CORE
- Agents with evidence, in production
- Customer service
- close to 1,500 tickets a day
- Copilot Studio
- Access to AI CORE through MCP
NXTGN AI CORE · Our AI product
AI using your knowledge and terminology.
A language model does not know your internal abbreviations or the relationships between your assets, components and business records. NXTGN AI CORE represents this context using a knowledge graph, glossary and taxonomy. Documents and databases supply the evidence; your specialists define terminology and relationships.
Explore NXTGN AI CORE →Your company’s synonyms, abbreviations and approved names.
Relationships between terms, assets, components and sources.
Models, embeddings and OCR on your servers or hosted on a dedicated NXTGN instance.
Which Microsoft offering fits your task?
We use Microsoft offerings where they support your process. Workplace Copilot, custom agents and individually developed AI applications need different building blocks.
Support work in Microsoft 365
Microsoft Copilot
Product documentation ↗Documents, email and meetings in the familiar workplace. Copilot Chat and Microsoft Copilot do not automatically have the same access to company data.
What we do for you
We assess suitable tasks, data access and adoption. Business teams test what actually improves their work.
Use AI in customer workflows
Copilot in Dynamics 365
Product documentation ↗Application-specific features supporting sales or service. Scope depends on the application, licence and availability.
What we do for you
We connect features to your CRM workflow, assess data quality and define approvals for customer responses or changes.
Build your own agents and workflows
Microsoft Copilot Studio
Product documentation ↗A low-code tool for agents with knowledge, tools and integrations. An agent can prepare work or execute permitted actions.
What we do for you
We design tasks, connectors, access and approvals. Exceptions and human fallback are part of delivery from the start.
Develop custom AI applications
Microsoft Foundry
Product documentation ↗An Azure platform for models, agents, tools and evaluation. Foundry is not one language model or a ready-configured business workflow.
What we do for you
We develop your application, integrate APIs and sources, and test quality, permitted actions and operations. Model and deployment are chosen for your data requirements.
We check licensing, processing and storage, regions, and preview or generally available features for the actual use case. An existing Microsoft licence does not replace this assessment.
Which workflow do you want to change?
Bring a specific workflow. Together we review handovers, exceptions and permissions: which tasks can an agent perform, which decisions stay with people, and what makes an outcome correct?
Discuss your workflow →