Custom Software and AI
Supporting complex processes with custom AI systems
We advise, develop, and integrate AI architectures that connect deeply with your existing processes. You define access rights, approval workflows, and appropriate European hosting options aligned with selected model and provider conditions. For companies focused on digital autonomy and protecting proprietary knowledge.
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Control through Architecture
Sovereignty over your data and processes is not created merely by the server location. We establish technical and organizational control points outside the actual AI model to manage risks in productive use.
Confidential Data and Internal Read Rights
A language model possesses no inherent awareness of permissions. The target architecture provides for a technical verification of source permissions prior to each data retrieval and the verification of the intended access protection with project-specific acceptance tests to control the inclusion of content in the prompt context.
- Adoption of existing user rights from existing systems
- Filtering of data prior to contact with the language model
- Technical permission checks prior to data retrieval to minimize internal information leakage
Unauthorized External Sending
To prevent uncontrolled data egress to external recipients, we restrict tools and interfaces to approved target systems using technical controls. As part of the security architecture, we verify the entire data path, including telemetry and provider endpoints.
- No unlimited email sending by the model
- Network-side blocks for external calls
- Clear definition and limitation of permitted data destinations
Consequential Actions and Approvals
AI systems can prepare processes, but should not execute business-critical actions without supervision. The system suggests actions or prepares documents. The binding approval is carried out by your technical experts in a specially designed interface.
- Mandatory human control for critical transactions
- Traceable logging of all machine suggestions
- Configurable thresholds for the degree of automation
Verifiable Answers and Uncertainty
The system compares answers directly with approved sources and presents evidence in a verifiable manner. If sufficient evidence is missing, the process is forwarded for manual review. However, an absolute absence of errors cannot be guaranteed.
- Check for the existence and assignment of source references
- Random validation of statements against reference data
- Labeling of insufficiently supported outputs in the audit log
Manipulation and Limited Tools
External inputs may contain attempts to prompt the AI to perform actions outside its purpose. We drastically limit the scope of action. The system only receives the tools it needs for the defined subtask. Additional filters analyze inputs prior to processing.
- Strict limitation of active AI tools
- Upstream filters for incoming system requests
- Architectural separation of data retrieval and code execution
Operations, Monitoring, and Provider Selection
Hosting in the EU does not yet guarantee sovereignty. We examine the conditions of the providers, their sub-processors, and the actual data flows. You decide on API models, dedicated hosting, or local systems. We establish monitoring, testing concepts, and clear exit strategies.
- Examination of data outflows and contractual provider conditions
- Setup of monitoring for system performance and operating costs
- Prepared technical scenarios for a model change
Enterprise AI in Practice: Reliable Relief for Established Core Processes
We integrate sovereign AI workflows directly into your existing systems to measurably accelerate labor-intensive routine processes.
IT and HR Support: Tier-1 Automation
Recurring standard inquiries tie up valuable support staff and delay simple information for the workforce.
Capture incoming requests from Microsoft Teams, Slack, email, or employee portals, verify user identity, and determine urgency.
Search internal knowledge sources such as ServiceNow, Confluence, and SharePoint for suitable solutions governed by access permissions.
Execute standardized routine actions such as password resets via existing interfaces without granting privileged permissions in an uncontrolled manner.
Forward complex cases with a prepared solution proposal to the specialist team and flag knowledge gaps for editorial review.
Business Value
Specialists are relieved of recurring routine tasks, requests are resolved more quickly, and the existing team handles a growing volume.
Control
Actions occur strictly within configured user roles, while specialist teams retain decision-making authority for escalations.
RFP and Tender Response
Extensive questionnaires on technology, security, and legal matters tie up subject matter experts for days in repetitive documentation work.
Capture tender documents in PDF, Word, or Excel formats and break them down into structured individual questions.
Match questions against approved knowledge bases and current technical documentation.
Generate a complete draft response with verifiable source references and highlighted gaps.
Involve subject matter experts specifically for missing content and feed newly approved answers back into the central knowledge base.
Business Value
Sales and specialist teams process more relevant tenders in parallel without permanently tying up valuable expert resources in daily operations.
Control
Every draft response undergoes manual review and final approval by the responsible business owners prior to submission.
Accounts Payable: Document Processing and 3-Way Matching
Manual capture and verification of incoming invoices against purchase orders and goods receipts causes high personnel effort and delays posting workflows.
Extract invoice data from PDF files and scans in a structured format and match it against vendor master data.
Verify line items against purchase orders and goods receipts in the ERP system based on defined business rules.
Verify amounts, tax rates, quantities, tolerances, and duplicates on a rule-based basis.
Pre-post matching invoices according to the approval matrix and route discrepancies with supporting evidence to the dashboard for manual resolution.
Business Value
Manual review effort decreases significantly, discrepancies become visible earlier, and early payment discount periods can be utilized more reliably.
Control
No automatic payment release; deterministic accounting rules govern the process, while the accounting team resolves exceptions and releases payments.
Contract Review: Third-Party Contract Analysis and Redlining
Initial review of standardized third-party contracts ties up scarce legal capacity needed for negotiations and strategic risks.
Analyze incoming vendor contracts or non-disclosure agreements against the stored internal legal playbook.
Transparently highlight deviations in key clauses such as liability, jurisdiction, or termination notices.
Insert approved alternative clauses from the legal library along with rationale as proposed revisions in edit mode.
Hand over the complete draft to the legal department so legal counsel can evaluate the overall contract in context.
Business Value
Preliminary review is accelerated considerably, allowing legal counsel to focus on negotiations and substantive risks.
Control
The legal department reviews the document in its overall context; AI suggestions serve solely for preparation without independent approval effect.
Software Development: Code Modernization and Maintenance
Legacy technical debt and repetitive maintenance tasks tie up experienced developers and slow down the further development of modern core products.
Analyze existing codebases, interfaces, and library dependencies in a structured manner.
Modernize outdated components in isolation and generate appropriate tests and technical documentation in preparation.
Automatically execute test runs, code quality metrics, and security checks within the existing CI/CD pipeline.
Provide a fully traceable pull request with documentation of all modifications for the development team.
Business Value
Maintenance backlogs are continuously reduced, while senior developers gain noticeably more capacity for value-adding product features.
Control
No automatic merge into the main branch; developers review and authorize every change in the regular peer review process before release.
These are illustrative use cases that clarify the scope of our integration services.
Possible Workflow in the Enterprise System
Hypothetical target vision of a supported procurement workflow from signal detection to confirmed booking.
Involved System
ERP System & IoT Sensors
Identify Bottleneck
The system detects an impending material shortage based on current inventory levels.
Control and Verification Mechanism
Automatic read access in the ERP via defined interfaces.
Illustrative target vision of an integrated workflow, no customer reference or automatic guarantee of success.
Layer Structure of an Enterprise AI
We separate the systems logically from one another. The actual language model is only one component of the architecture. The control of access and processes remains in the software that we build for you.
Control Layer
The heart of the architecture. This is where the authorization check, the routing of requests, and the enforcement of your business rules take place, even before a language model is contacted.
This is a simplified model. The actual design depends on your IT security guidelines.
Target Architecture in Comparison
Comparative analysis for management evaluating standalone standard AI chatbots versus integrated, custom enterprise AI architectures.
This scenario compares standalone chatbots without internal integrations against custom enterprise target architectures. Commercial standard plans may also offer access rights, connectors, or privacy controls, depending on the provider, plan, and configuration.
Knowledge & Systems
Use of corporate data and connection of internal specialized systems.
Corporate Knowledge & TimelinessShow DetailsClose DetailsStandard AI ChatbotStandalone chat with manual file uploads, lacking direct connection to centralized corporate knowledge repositories.Custom Enterprise AI SystemTargeted access to approved corporate databases, wikis, and current document versions.
Business Value
Employees access verified internal information sources instead of isolated single files.
Practical Example
Inquiries about internal guidelines are answered based on the currently approved version in the company wiki.
Implementation & Framework Conditions
Set up database retrieval, define update intervals, and technically connect access rights.
Source Evidence & TransparencyShow DetailsClose DetailsStandard AI ChatbotCitations depend on prompt context and manual checking without automated verification against source documents.Custom Enterprise AI SystemExact references to paragraphs, page numbers, and document versions with technical validation.
Business Value
Decision-makers can specifically verify statements made by the system in the underlying source text.
Practical Example
For contract questions, the application highlights the specific paragraph in the stored document repository.
Implementation & Framework Conditions
Integrate referencing logic, anchor citation rules, and perform validation tests.
Specialized System ConnectionShow DetailsClose DetailsStandard AI ChatbotOperates as an isolated tool without direct integration into specialized core enterprise systems.Custom Enterprise AI SystemConnection of ERP, CRM, and database systems via defined interfaces.
Business Value
Reduces manual transfer of data between AI applications and operational systems.
Practical Example
The system reads current inventory levels directly from the ERP system without manual file export.
Implementation & Framework Conditions
Connect interfaces, set authentication, and coordinate data structures.
Connected ProcessesShow DetailsClose DetailsStandard AI ChatbotAssists with conversational tasks without triggering multi-step workflows across independent internal software systems.Custom Enterprise AI SystemOrchestration of multi-stage workflows across specialized departments and specialized systems.
Business Value
Multi-stage business processes are supported from data capture to approval preparation.
Practical Example
A complaint is recorded in the CRM, triggers a check in the ERP, and prepares customer service.
Implementation & Framework Conditions
Integrate workflow engine, define process steps, and test system transitions.
Rights & Actions
Access controls, identity verification, and authorization of operational interventions.
Identity & RolesShow DetailsClose DetailsStandard AI ChatbotUser access relies on the service's standard administrative settings, while specific enterprise role alignments are handled manually outside the application.Custom Enterprise AI SystemConnection with corporate identity provider to enforce existing user rights.
Business Value
Employees only get access to data for which they are authorized in the company.
Practical Example
Sales representatives do not receive information about confidential salary data from the HR department.
Implementation & Framework Conditions
Integrate SAML/OIDC login and check access rights server-side for data queries and actions independent of the model.
Data MinimizationShow DetailsClose DetailsStandard AI ChatbotUsers rely on standard platform safeguards, while staff manually manage sensitive enterprise inputs outside custom upstream pseudonymization workflows.Custom Enterprise AI SystemTechnical filtering methods outside the language model for pseudonymization of sensitive data.
Business Value
Sensitive personal or financial data is purposefully reduced prior to model transmission.
Practical Example
Real names and account numbers are replaced by system placeholders before calling the model.
Implementation & Framework Conditions
Build filter rules outside the language model and provide for regular checks.
Action Limits & ApprovalsShow DetailsClose DetailsStandard AI ChatbotActions and approvals depend on the selected feature set and configuration. Company-specific approval rules must be configured and reviewed separately.Custom Enterprise AI SystemDefined stopping points before consequential actions with mandatory human approval.
Business Value
The AI system prepares steps, but does not execute critical actions on its own authority.
Practical Example
A drafted contract is only sent after approval by the responsible specialist.
Implementation & Framework Conditions
Program approval barriers in the backend and anchor authorization limits.
Traceability & AuditShow DetailsClose DetailsStandard AI ChatbotLogging and retention follow standard provider settings, while central enterprise audit alignment is coordinated outside the application.Custom Enterprise AI SystemLogging of required events with retention rules and access and deletion concept.
Business Value
Decision steps and human approvals remain traceable for internal audit purposes.
Practical Example
During an audit, the system logs are used to prove who approved an order.
Implementation & Framework Conditions
Set up logging servers, restrict access rights, and set deletion periods.
Data Sovereignty & Models
Storage locations, training usage, and avoidance of unilateral dependencies.
Training UsageShow DetailsClose DetailsStandard AI ChatbotData usage for model training depends on the specific provider, subscription tier, and configuration settings.Custom Enterprise AI SystemContractually and technically defined exclusion of the use of proprietary corporate data for the provider's model training.
Business Value
Confidential business information does not flow into the general training of the model provider.
Practical Example
Entered texts are not used by the provider for general model training; storage and retention periods are regulated separately.
Implementation & Framework Conditions
Conclude a data usage agreement and set API settings accordingly.
Storage & Processing LocationsShow DetailsClose DetailsStandard AI ChatbotData hosting operates across available provider cloud regions, governed by standard commercial vendor infrastructure rather than custom tenant deployments.Custom Enterprise AI SystemDefinable storage and processing locations taking backups and infrastructure into account.
Business Value
Supports compliance with internal governance guidelines through selectable infrastructure modules.
Practical Example
Data processing and logging take place in designated European data centers.
Implementation & Framework Conditions
Select cloud regions, check and define data paths including fallback services.
Model Choice & DependenciesShow DetailsClose DetailsStandard AI ChatbotOperation is tied to the vendor platform without architectural flexibility to replace underlying models.Custom Enterprise AI SystemConceptually interchangeable models after prior quality check and test phase.
Business Value
Enables adjustments in the event of technical advancements or changed market conditions.
Practical Example
A model is replaced by a specialized model after thorough regression tests.
Implementation & Framework Conditions
Develop abstraction layer in the backend and build automated test suites.
Operations & Exit StrategyShow DetailsClose DetailsStandard AI ChatbotOffboarding and data extraction depend on standard commercial contract terms and the selected provider's built-in export features.Custom Enterprise AI SystemAgreed configurations, administrative rights, and defined handover and export paths.
Business Value
Maintains sovereignty over developed process logics and allows for later system adjustments.
Practical Example
Process descriptions and prompt configurations are backed up in a proprietary repository.
Implementation & Framework Conditions
Structure admin rights, create backup concept, and secure handover.
Quality & Operations
Reliability, testing procedures, error handling, and cost structure.
Technical Tests & AcceptanceShow DetailsClose DetailsStandard AI ChatbotOutput quality relies on vendor product testing and manual reviews, while company-specific acceptance criteria are evaluated outside systematic automation.Custom Enterprise AI SystemSystematic functional tests and regular regression tests prior to productive release.
Business Value
Increases the reliability of system outputs through structured quality controls.
Practical Example
Before system updates, test cases verify whether calculations and source evidence are output correctly.
Implementation & Framework Conditions
Build evaluation sets, define test criteria, and anchor acceptance processes.
Errors & EscalationShow DetailsClose DetailsStandard AI ChatbotUncertain responses require user vigilance without integrated automated plausibility checks or enterprise escalation workflows.Custom Enterprise AI SystemExternal plausibility checks and defined escalation paths in case of uncertainties or system errors.
Business Value
Incorrect or incomplete details are better intercepted by downstream checks.
Practical Example
In the event of incomplete source details, the system marks the result and forwards it for review.
Implementation & Framework Conditions
Program validation rules and anchor escalation paths in the workflow.
Monitoring & SupportShow DetailsClose DetailsStandard AI ChatbotAvailability and support levels are governed by the chosen commercial plan's standard service agreements and vendor commitments.Custom Enterprise AI SystemSystem monitoring, technical support, and agreed service levels for ongoing operations.
Business Value
Enables the detection of operational anomalies as well as the organized assignment of responsibilities and reactions.
Practical Example
A monitoring system notifies the IT department when response times of interfaces increase.
Implementation & Framework Conditions
Set up monitoring tools, clarify responsibilities, and define operating contract.
Implementation & Total CostsShow DetailsClose DetailsStandard AI ChatbotCosts include subscriptions or usage-based pricing alongside potential effort for basic setup and manual post-processing of generated results.Custom Enterprise AI SystemTotal cost scope includes development, system integration, model operation, maintenance, and controls.
Business Value
Investments are based on the concrete process value and the desired degree of control.
Practical Example
A company invests in AI integration to reduce processing times in purchasing.
Implementation & Framework Conditions
Perform cost-benefit analysis, estimate integration effort, and plan operating budget.
Scenario comparison of architectural archetypes. Target capabilities and operational controls require project-level design and validation.
Process for Sovereign Enterprise AI
Architecture and Value Analysis
We evaluate economic and technical aspects to design a tailored AI foundation for your company before implementation begins.
Iterative Development
We build your sovereign AI solution in agile cycles. This approach allows the software to be gradually adapted to your specific business requirements.
Testing, Security and Integration
We rigorously test data access, answer quality and operational limits while blocking unauthorized actions. This is followed by business acceptance in your IT landscape.
Planned Operation
After successful integration, we handle the operation and monitoring of your solution, exactly within the contractually agreed scope.
Frequently Asked Technical Questions
What about the training of the models with our data?
The use of your business data for the provider's general model training is contractually excluded and secured through appropriate API and operational settings. Because terms vary, this is verified and established specifically for the selected model and vendor prior to deployment. Model training and data retention are treated as separate matters.
How do you ensure that the system does not generate false information?
We ensure quality through clear source references and regular functional tests. In the event of remaining uncertainties, a targeted review by subject matter experts takes place. However, there is no absolute guarantee for error-free outputs.
Can we switch the solution to a different AI model later?
Yes, we design the architecture modularly. The orchestration layer and data source connections are decoupled from the language model itself. This facilitates transitioning to newer or more cost-effective models once compatibility and quality testing for your specific use case are complete.
What preliminary work is required in our IT infrastructure?
For machine use, the data to be connected must be available in a usable form. Together with your IT, we identify the relevant source systems, check existing interfaces, and evaluate the structure of the existing documents. Building on this, we plan the necessary data pipelines.
Your Path to Your Own AI System
Talk to us about your complex processes. We evaluate technical feasibility, outline a sensible implementation, and show how you retain control over your data and workflows.