AI Solutions

·FOUR SERVICE BUILDING BLOCKS

AI solutions that fit your processes.

We build AI assistants, automations and data pipelines so they are securely integrable, traceably governable and usable for real business processes.

Custom AI Engineering

Architecture design, AI backends, data pipelines, ERP/CRM integration, custom models.

LLM & Assistants

Model selection, knowledge assistants that answer only from your own documents (RAG), role-based access, prompt architectures.

Process Automation

Document processing, workflow engines, API integrations, decision support.

AI Governance

Access control, monitoring, on-prem options, EU AI Act readiness, audit-ready documentation.

·OUR AI SOLUTIONS

AI solutions for your industry.

From clinical documentation to fraud detection: MiRA is available today, the other use cases we build from the same components for your industry. GDPR-compliant, fully on your premises or sovereignly hosted in Germany.

MiRA

Available solution

Hospitals & health centers · Medical Intelligence Recording Assistant

Clinical AI documentation. MiRA listens to every doctor-patient conversation and creates a structured medical report in under 60 seconds. Fully on-premises, no audio ever leaves your hospital.

See MiRA in detail →

Law firms

Contract & document AI

Clause extraction, risk scoring and full-text search across contracts and files. Rapid review against template contracts.

Insurers

Claims & document processing

Automatic intake, classification and anomaly or fraud detection in claims.

Public sector

Secure knowledge assistants

Assistant that draws its answers from your own records and cites the source (RAG), with role-based access and GDPR anonymization. Fully auditable.

Industry

Anomaly detection & forecasting

Early warning from sensor and machine data, plus demand and sales forecasts on your own data.

Banks

Compliance & fraud detection

Rule checks against DORA, BAIT, GDPR and the EU AI Act, detection of transactions that deviate from the normal pattern (anomaly detection), and document AI.

Other industries

Custom AI solution

Your industry not listed? We build GDPR-compliant AI solutions for your specific use case.

Discuss an AI service →

·AI TEST AUTOMATION

Test AI before it creates risk.

We test ML models, language models (LLMs) and data pipelines automatically: quality, security, drift (a gradual decline in performance during operation), bias (systematic distortion) and verifiability, before go-live and in operation.

ML Models

Performance, drift, and robustness as a continuous process, not a one-off acceptance test.

Performance & generalization
Stability
Drift detection
Overfitting / Underfitting
Robustness
Versioning
Documentation

You see before go-live and in operation whether the model is degrading, and get the evidence for the audit.

LLMs

Systematically secure against hallucinations (fabricated answers), prompt injection (manipulated inputs that redirect the model), output inconsistency, and data exposure.

Prompt tests
Hallucination checks
Prompt-Injection
Data exposure
Access control
Output guardrails
Logging

Language models only go live once they demonstrably reveal no sensitive data.

Data Foundation

Completeness, bias, and distribution shifts as the basis for any reliable model output.

Completeness
Outliers & inconsistencies
Label quality
Distribution shifts
Bias risks
Data drift
Versioning

You spot faulty or biased data before the model draws the wrong conclusions from it.

·METHODOLOGY

From data foundation to production.

Structured approach, from risk classification to continuous monitoring in production.

01Scope & Risk

Use case, model type, data sources, risk class, test goals.

02Test design

Test cases, metrics, thresholds, adversarial scenarios.

03Validation

Run ML, LLM, data, and pipeline tests automatically.

04Monitoring

Drift, output behavior, performance, and anomalies in production.

05Reporting

Technical results, management summary, and audit evidence.

06Improvement

Feed findings back into data, prompts, guardrails, or architecture.

Every test is measurable, reproducible, and documented as evidence for governance and audit.

Configure AI Test Automation →

USE CASES

Situations where we support you

AI Solutions

Roll out internal AI assistants safely

Problem: Employees should work faster with internal knowledge without sensitive data flowing into external systems uncontrolled.
Approach: We design AI assistants with clear data spaces, roles, permissions, integration points, and governance.
Benefit: More productivity through AI, with better control over data, access, and results.

AI Solutions

Integrate LLMs and AI into existing IT processes

Problem: AI projects often stall as pilots because integration, data quality, process connection, and security requirements don’t align.
Approach: We support with LLM integration, secure data pipelines, process automation, and technical architecture.
Benefit: Usable AI solutions, not isolated experiments.

AI Solutions

Process documents and automate workflows

Problem: Contracts, reports, forms, and emails consume manual capacity, even though many steps are rule-based and traceable.
Approach: We deploy LLM and workflow components to classify documents, extract data, route tasks, and write results back into existing systems in a structured way.
Benefit: Tangible relief for recurring processes, with traceable handling of sensitive content.

AI Solutions

Connect ERP, CRM, and knowledge data with LLMs

Problem: Valuable knowledge is scattered across ERP, CRM, wikis, and file shares. General-purpose models can’t use this data without risk.
Approach: We build retrieval-augmented generation architectures with clear data spaces, permissions, source references, and audit logs. Sovereign-hosted on request.
Benefit: Answers based on your own data, with traceable provenance and controlled access.

AI Solutions

Configure AI Solutions →

·CUSTOM MODELS

Custom Model Development.

Not every task is solved by a generic model. For classification, forecasting, anomaly detection (deviations from the normal pattern) or decision support, we train models on your own data.

Failure early warning from machine data
Fraud patterns in claims
Route incoming mail to the right case automatically

·APPROACH

From idea to a production AI solution.

Five phases in which architecture, data, models, governance and operations are considered together.

01Analysis

Clarify use case, data situation, risks and target vision.

02Architecture

Plan system landscape, data pipelines, models and integrations.

03Development

Implement AI backends, assistants, automations or custom models.

04Governance

Integrate roles, permissions, logging, monitoring and documentation.

05Operations

Prepare deployment, maintenance, quality assurance and further development.

For validation and quality assurance, AI Test Automation can be connected as a complement.

View AI Test Automation →