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On-Premise AI

AI workflows — cloud-based, hybrid or entirely on your own infrastructure.

How AI is kept under control inside a process, and where it runs: from the control layer between your systems and the model to the three deployment modes.

YOUR INFRASTRUCTUREDMSERPEmailConpeak AI LayerLocal modelOPTIONALApproved cloud modelWhere the boundary runs is decided by the process — not by a model provider.

AI in business processes

AI becomes valuable when it becomes part of a working process.

A language model on its own is not yet a reliable business solution. Conpeak builds the system around it – with clear rules, controlled approvals and traceable results.

Controlled flow

  1. 01Intake
  2. 02AI processing
  3. 03Validation
  4. 04Approval
  5. 05System action
  6. 06Audit log

Control instead of black box

Controlled execution

AI works in clearly defined steps with limited tools – not as uncontrolled autonomy.

Human approval

Critical actions are prepared by the system and reviewed by employees before they are executed.

Clear permissions

Each workflow may only access the data and systems it needs for its task.

Traceable results

Every step is logged. It always stays visible what happened – and why.

Technical details and further use cases

The system around the model

  • Data access
  • Tools
  • Permissions
  • Business rules
  • Validation
  • Human-in-the-loop
  • Monitoring
  • Evaluation
  • Error handling
  • Auditability

Concrete use cases

Processing incoming orders

  • Read emails and attachments
  • Extract line items and quantities
  • Check customer data and products
  • Detect missing information
  • Prepare the order for approval

Coordinating service requests

  • Classify the request
  • Identify the affected machine
  • Retrieve history and documentation
  • Prepare a suggested solution
  • Create or escalate a ticket

Providing operational information

  • Combine information from several systems
  • Answer questions in natural language
  • Detect deviations and missing data
  • Create daily summaries

Not every company can or wants to send confidential data to external AI services.

Conpeak builds AI systems that can run entirely inside your own infrastructure if required — from document and data access through to model inference itself.

What can run locally

Inside your infrastructure

Data

  • Documents and company data
  • User and permission data

Preparation

  • Document processing / OCR
  • Embeddings
  • Semantic search index
  • Vector database

Query

  • Retrieval
  • Reranking
  • Prompts

Model

  • Language model
  • Answers

Record

  • Chat history
  • Audit logs

No external model processing required

Applies to the fully local configuration

Three deployment modes

On-premise

Fully local processing

The complete AI stack can run inside your own infrastructure.

  • Confidential data stays in the controlled environment
  • No external model API required
  • Permission checks in your own system
  • Predictable architecture
  • Operation without external AI dependencies is possible

Hybrid

Local data, optional cloud models

Documents, search index, permissions and retrieval stay local. Approved parts of selected requests can optionally be routed to cloud models.

  • Retrieval stays local
  • Data minimisation before anything leaves
  • Optional pseudonymisation or redaction
  • Policy-based model routing
  • Separate policies per process and data class

Cloud

Maximum flexibility and scalability

Approved cloud models can be used where your data classification and security requirements allow it.

  • Access to current frontier models
  • Elastic scaling
  • Lower local hardware requirements

The architecture follows the process — not a single model provider.

Have an on-premise AI use case reviewedSee the control layer in the Agent Lab

Architecture

Access is decided before the model.

A dedicated layer sits between your business systems and the language model. It answers who is allowed to see what, which content enters a request at all, and which model is allowed to answer it.

Business systems

  • DMS
  • SharePoint
  • File server
  • ERP
  • CRM
  • Outlook / email
  • Internal databases

Controlled layer

Conpeak AI Layer

  • Authentication
  • Permissions
  • Retrieval
  • Embeddings
  • Audit
  • Model routing
  • Policy enforcement

Possible model destinations

  • Local open-weight model
  • Approved EU or cloud model
  • Other approved LLM providers

Permissions and data access are controlled by the system outside the language model.

Control stays in the system

  • Access rights are checked before AI processing.
  • The language model does not decide on permissions.
  • Data sources and model access can be logged.
  • Different processes can be given different AI policies.
  • Local and external models can be governed separately.

Model independence

The model is replaceable

Conpeak does not build AI systems around a single model provider. Depending on the requirements, local open-weight models or approved cloud models can be used. Data access, permissions, retrieval, business logic, monitoring and auditability remain part of the controlled system architecture.

Use cases

Where on-premise AI can make particular sense

The common factor is not the industry but how confidential the underlying documents are, and how precisely it has to remain traceable who accessed what.

Internal knowledge search

Questions across internal documents, policies, contracts and company knowledge.

Document analysis

Search, summarise and systematically evaluate large document holdings.

Confidential contract and case analysis

Analyse sensitive documents without requiring external AI processing.

Technical knowledge

Make manuals, service reports, specifications and quality documentation usable.

Research and development

Use internal technical information and intellectual property in controlled AI workflows.

Regulated processes

Apply AI where permissions, auditability and traceable data flows matter most.

Typical industries

  • Law firms
  • Tax advisory and auditing
  • Industry and mechanical engineering
  • Engineering
  • Insurance
  • Sensitive B2B services
  • Research and development

Common questions

Does the AI have to run entirely locally?

No. Depending on the requirements, the architecture can be fully local, hybrid or cloud-based.

Do company documents stay local?

In an on-premise architecture, documents, search index, embeddings, prompts and model inference can remain inside your own infrastructure.

Can cloud models still be used?

Yes. In a hybrid architecture, approved cloud models can optionally be integrated.

Is Conpeak tied to a particular AI provider?

No. The architecture is designed to be as model-independent as possible.

Can the solution connect to existing systems?

Yes. Typical integration targets can be DMS, file servers, SharePoint, ERP, CRM, email systems and internal databases.