HIP Integrator
AI-native data integration. Deterministic by design.
The HIP Integrator is an AI-assisted data integration tool for health data. It makes data integration and migration between CDRs and existing systems faster and more cost-effective – without compromising control, transparency or data sovereignty. Alongside conventional message-based system integration using HL7 v2 and FHIR, it also supports direct data pipelines between existing systems and CDRs.
Benefit
Turn data into insight – faster
Integrate your systems in just days or weeks rather than months – with AI-assisted analysis and deterministic execution.
From complex source systems to usable data
The HIP Integrator unlocks health data from existing systems and transfers it into open, interoperable data models. AI supports source-system analysis and mapping proposals. Experts review and approve the results; the HIP Integrator then processes data deterministically and traceably.
This creates a reliable basis for making data available sooner for care delivery, analytics, research and digital applications.
Challenge
The challenge of existing systems and their data
Many healthcare organisations find it difficult to unlock health data from existing systems and use it to meet their organisational objectives. Hospital information systems, patient data management systems and departmental applications are built on complex, vendor-specific data models, rarely offer standardised interfaces and are often documented only in part.
As a result, data is distributed, difficult to locate and interpret, and of limited use for interoperability, analytics or AI. Integration projects demand extensive manual work and highly specialised expertise – and often take months.
Solution
Accelerate health data integration with the HIP Integrator
The HIP Integrator is an AI-native integration tool that transforms even complex health data from existing systems into interoperable formats such as openEHR and FHIR, while retaining full control over data processing. It combines AI-assisted analysis with purpose-built tools to accelerate data integration, shorten time to value and reduce project risk.
How the HIP Integrator works
The HIP Integrator ingests and analyses sample messages, database schemas, system documentation and clinical forms to build a detailed semantic understanding of source systems. You decide explicitly whether AI agents see metadata only or are allowed to access real data, and – where necessary – whether that access is limited to a defined data subset.
Using openEHR as a semantically structured target model, the HIP Integrator identifies data relationships, generates mappings and creates data pipelines. Every pipeline remains fully editable, enabling continuous human-in-the-loop validation, transparency and full control throughout the integration process.
The HIP Integrator brings data into the platform. Once standardised and semantically annotated, that data is stored in the HIP Clinical Data Repository (HIP CDR) and made available to applications through open interfaces. HIP Insights can use it for analytics, while HIP Clinical supports clinical applications. The quality of the mapping determines the reliability of every downstream use case.
Built specifically for health data integration.
Your benefits
- Deterministic data flows that are secure, transparent, traceable and fully auditable
- Use AI while preserving data sovereignty and compliance
- Shorten integration projects from months to weeks
- Migrate historical data and establish ongoing data flows using the same mapping
- Reduce manual effort in analysis and mapping
- Reuse integration knowledge across projects and sites
- Retain critical integration knowledge independently of individual team members
Speed without control? Not an option in healthcare.
AI where it helps. Determinism where it matters. Data access only when a person approves it.
Many tools place AI directly in the production data flow. Early results can be generated quickly, but in clinical environments they can require substantial effort to validate, trace and audit.
The HIP Integrator takes a different approach. AI supports analysis, interpretation and mapping proposals during the design phase. Productive data processing runs through a deterministic, standardised ETL engine – reviewed and approved by integration teams before go-live, then reproducible and auditable in operation.
Key features
AI-assisted source analysis
Automatically analyses source systems and builds a structured understanding of the clinical data they contain.
Data access on request
If an AI agent needs real data to complete a mapping, it requests access and explains why. Access is granted selectively by people – for example, for defined patient IDs.
AI-assisted mapping
Generates mapping proposals for openEHR and FHIR, while integration specialists retain full control through review and approval.
Deterministic execution
Approved mappings are executed through a standardised ETL engine. AI is not part of the production data path.
Production data flows via HL7 v2 and FHIR
A configurable integration facade based on HL7 v2 and FHIR. It supports transactions such as patient merges for synchronisation with the hospital information system, as well as outbound FHIR and HL7 v2 interfaces.
Monitoring and validation
Identifies data-quality issues, schema changes and runtime errors before they affect downstream systems.
Experts and AI working together
Domain experts and AI agents work side by side in a shared environment, directly on integration tasks.
Managed and self-hosted LLMs
Supports secure, GDPR-compliant providers as well as self-hosted LLMs. AI processing can remain within your own infrastructure, preserving data protection and data sovereignty.
Data protection and regulatory assurance
Clinical environments require more than functionality. They require compliance. The HIP Integrator meets both requirements:
- Productive data processing runs without AI. Approved mappings are executed deterministically and remain fully auditable.
- At the start of a project, you define whether AI agents may access the connected system. Full access is appropriate for test and integration environments using synthetic data. For systems containing real patient data, the closed mode is available.
- In closed mode, agents work with schemas, documentation and user interfaces. If this is insufficient for a mapping, the agent makes the limitation explicit and requests access rather than receiving it by default. Your domain experts can then grant access selectively – for individual fields or defined patient IDs. The decision remains with people.
- Where required, AI processing can run entirely within your infrastructure using self-hosted open-weight models. Your data then remains on your premises. Alternatively, processing can take place under a data-processing agreement.
- All AI interaction points are designed to meet the transparency requirements of Article 50 of the EU AI Act.
HIP Integrator: Insights into the solution
Run discovery and confirm that tables are assigned to the appropriate openEHR archetypes.
Import documents, screenshots or terminologies that support the development of mappings.
Following discovery, define mappings and test the implementation.
An AI-native environment for hospital and regional integration teams.
Current use cases
Migrate historical data and establish ongoing data flows
Faster, with less manual effort
Migrate clinical data from proprietary or insufficiently documented systems to openEHR and FHIR with substantially less manual analysis and mapping effort. The same approved mapping can then support the ongoing data flow from the same source system.Research and analytics
Built on structured clinical data
Make structured clinical data available for analytics platforms, quality initiatives and research programmes.AI-ready health data
For analytics, automation and innovation
Prepare clinical data for AI applications by transforming fragmented data from existing systems into structured, interoperable formats.With the HIP Integrator, we give integration teams an AI assistant for the demanding analytical work – while people remain clearly in control of every decision that truly matters.
A controlled, transparent and scalable approach to interoperability in healthcare.
Designed for
Hospitals and hospital groups
Unlock data from existing systems without replacing them, while building integration knowledge that can be reused in the next project and at the next site.
Solutions for hospitals and hospital groupsSystem integrators
Plan integration projects with greater certainty because analysis and mapping are no longer dependent on the experience of individual people, but on a reusable knowledge model.
Health regions and data spaces
Bring data from many organisations into a shared model, with a mapping pipeline created once for each source system and kept transparent for all participants.
Solutions for health regions and data spacesSoftware providers
Use interoperability as a component rather than building and maintaining HL7 v2 and FHIR integrations separately for every customer.
Solutions for software providers