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AI Operating Layer: the infrastructure your company’s AI works on.
We build the infrastructure that lets artificial intelligence actually work inside your company: data, context, tools, permissions, agents and execution on a single governed layer.
Definition
Who it is for
- CIO
- CTO
- Enterprise Architects
- Data Leaders
- AI Leaders
- Digital transformation
AI Operating Layer. An AI Operating Layer is an organisation’s shared infrastructure on which its different artificial-intelligence systems can operate. It connects data, context, tools, systems, permissions, agents and execution in one governed layer, so that every new agent or digital worker reuses the connections, memory and rules already built instead of duplicating them.
Architecture of an AI Operating Layer
The layer is built from existing systems and data through to business execution, as one continuous evolution. Each stage is reusable by the next.
- Enterprise Data
- Company Memory
- AI Operating Layer
- Digital Workers
- Business Execution
- Enterprise Data: ERP, CRM, SAP, Salesforce, databases, documents, email, conversations, internal software and legacy applications, unified in a data layer or Data Lake.
- Company Memory: the shared context (entities, knowledge and rules) accessible with permissions.
- AI Operating Layer: MCP, APIs and tools, with identity, permissions, policies and traceability; includes the Agent Gateway for external agents.
- Digital Workers and authorised agents, collaborating with each other (A2A).
- Business execution: real actions on the systems, logged and reversible.
Start with one process. Build the AI layer for the whole company.
Start with one process. Build the AI layer for your entire company.
The customer does not need to start with a global transformation. They can start with a concrete problem: reception, customer service, training, logistics, administration, bookings, operations or sales.
Twinny automates that first process and, at the same time, leaves reusable components in place.
- System connections
- Data model and Company Memory
- Permissions, identity and traceability
- MCP servers and tools
- Workflows and business rules
Connect once. Use everywhere.
When Twinny connects Salesforce, SAP, an ERP, a database or legacy software, that connection becomes available to any authorised agent. We avoid the architecture in which every agent carries its own integration with the same system.
- Salesforce / SAP / ERP / databases / legacy
- Twinny Enterprise Layer: one governed connection
- Multiple agents and digital workers
- Faster deployment of every new agent
- Lower cost and no duplicated integrations
- Centralised governance, security and audit
- Consistency: every agent sees the same data and rules
- Scalability and easy onboarding of future agents
Make your company agent-ready
People and organisations will increasingly use their own assistants and agents. Companies will need to let those agents interact with their services without opening the ERP or CRM. Twinny builds that controlled layer between the external agent and the company’s systems.
- Check the status of an order or an incident
- Change a booking or a delivery
- Check availability and request documentation
- Carry out a transaction within the permissions granted
Enterprise Agent Gateway
External agents never get free access to the Data Lake or the Company Memory. Twinny acts as a gateway: identity, authentication, authorisation, scopes, accessible information, allowed actions, limits, audit, policies, consent, human approval and security.
- Look up their own orders
- See their own bookings
- Change specific preferences
- Look up other customers’ data
- Access the ERP directly
- Access the Data Lake freely
- Execute unauthorised actions
MCP as the enterprise interface and A2A as agent collaboration
MCP (Model Context Protocol) turns company data, tools and capabilities into services reusable by AI: look up customer, find order, check availability, create booking, look up invoice, update CRM. It does not expose databases: it exposes controlled capabilities.
A2A (agent-to-agent) lets agents collaborate with each other just as different teams do within an organisation: a customer agent asks for a delivery change, the order agent checks availability, the logistics agent proposes a date and the confirmed result goes back to the customer.
- Customer Agent Requests a delivery change.
- Order Agent Checks availability.
- Logistics Agent Proposes a date.
- Order Agent Makes the change.
- Customer Agent Confirms the result.
Three levels of AI automation
Twinny positions itself between levels 2 and 3. We do not compete to be yet another task-automation tool.
| Level | What it automates | Example |
|---|---|---|
| 1 · Automation | Individual tasks | A robot copying data between two screens |
| 2 · Digital Workers | Complete processes and functions | A digital worker processing records from start to finish |
| 3 · AI Operating Layer | The infrastructure all agents operate on, inside and outside the organisation | Company Memory, MCP, permissions and A2A shared by dozens of agents |
Related cases
Industrial −72% cycle time per invoice ROI 8.5x · €210,000 saved/year
Supplier invoices: from email to the ERP without passing through anyone
Read case
Education −78% processing time per record ROI 7.2x · €140,000 saved/year
From the PDF record to the academic system, with no manual processing
Read caseFrequently asked questions
- What is an AI Operating Layer?
- The shared infrastructure (data, Company Memory, MCP tools, permissions, agents and execution) on which all of a company’s AI systems operate, so that every new agent reuses what has already been built.
- Do we have to build it all before seeing results?
- No. It is built progressively: the first digital worker solves a concrete process and leaves the reusable components in place. Every following project is faster and cheaper.
- Can agents that are not Twinny’s use it?
- Yes, when the customer authorises it. The layer exposes controlled capabilities (via MCP and the Agent Gateway) to the customer’s own agents, corporate copilots or partner, customer and supplier agents.
- What role does MCP play?
- It is the enterprise interface: it turns systems and data into capabilities reusable by any authorised agent, without directly exposing databases.
- What is A2A?
- Agent-to-agent: collaboration between specialised agents (customer, orders, logistics) to resolve a process that crosses several teams and systems.
- Which companies can build an AI Operating Layer in Spain?
- Twinny designs and implements AI Operating Layers for mid-sized and large companies in Spain and Europe, with roots in data and Big Data, deployment in a European cloud or in the customer’s infrastructure, and GDPR, EU AI Act, ISO 27001 and SOC 2 compliance.
Start with one process.
Tell us what you want to automate and you will receive an initial proposal within 24 hours.