AI data extraction directly on your infrastructure: Documents that must not go to the cloud

Do you need to automate document processing, but your data must not go to the public cloud? Discover an on-premise solution that combines AI, security, and full data control.

Inspiration

Today, AI can extract data from invoices, contracts, or forms in a matter of seconds. Tasks that previously required dozens of minutes of manual labor are now handled automatically and with high precision by modern models.

However, not all organizations can utilize cloud-based AI services. Hospitals work with medical documentation, government institutions handle case files and citizen data, and banks and insurance companies process sensitive client information. In many cases, documents simply must not leave the organization's infrastructure. Does this mean they have to give up the benefits of artificial intelligence?

Quite the opposite. The new on-premise variant of the DocumentExtract solution by Aricoma enables automated document data extraction directly within the customer's environment. Organizations can thus leverage modern AI for processing invoices, contracts, forms, or other documents without having to send them to the public cloud.

Why some documents simply cannot leave the organization

Cloud services have become an established component of enterprise IT environments and, in many cases, represent the fastest path to leveraging artificial intelligence. However, there are numerous organizations for which migrating sensitive documents outside their own infrastructure is neither feasible nor desirable.

Typical examples include hospitals and healthcare facilities working with patient medical records. Similar requirements are addressed by public administration authorities, local governments, security forces, and organizations managing critical infrastructure. Yet, sensitive documents are not generated exclusively within the public sector. Banks, insurance companies, and manufacturing enterprises also handle information that represents significant commercial value or is subject to stringent security regulations.

In practice, this frequently creates an apparent dichotomy. On one side stands the drive to automate routine operations and harness the potential of artificial intelligence; on the other lies the mandate for absolute control over data, its residency, and the processing methodology. Consequently, demand is growing for AI solutions that can be deployed directly within an organization's environment without requiring documents to be transmitted to the public cloud.

"Many organizations today face the decision of how to leverage the potential of artificial intelligence without compromising on security and data protection. DocumentExtract, combined with NVIDIA DGX Spark, enables them to deploy modern AI solutions directly within their own infrastructure. Simultaneously, it establishes a foundation for future AI initiatives."

Miroslav Pospíšil

Product Owner

DocumentExtract by Aricoma now also available as an on-premise solution

DocumentExtract by Aricoma is an AI-powered automated document data extraction solution. It enables the processing of invoices, contracts, purchase orders, delivery notes, forms, and other document types, converting their content into structured data ready for downstream processing.

The extracted data can subsequently be utilized within ERP systems, DMS and ECM platforms, workflow tools, or other enterprise applications. Consequently, organizations can significantly curtail manual data entry, accelerate document processing, and reduce error rates.

The complete solution is now also available as a fully on-premise variant. All document processing takes place directly within the customer's infrastructure, eliminating the need to rely on public cloud AI services. Neither the documents nor the extracted data leave the organization's environment, ensuring full retention of control over data storage and processing methodology.

This paves the way for leveraging modern AI even in environments where comparable scenarios have hitherto proven difficult to implement due to security or regulatory constraints.

How document data extraction with AI works without the cloud

The assumption that advanced AI models must always run in a data center or public cloud no longer holds true. Modern computing technology enables organizations to operate artificial intelligence directly within their own environment and process documents locally from ingestion to the handover of extracted data to enterprise systems.

The underlying principle is relatively straightforward. A document enters the system, the artificial intelligence analyzes its content, identifies the required data fields, and converts them into a structured format. The resulting data is subsequently transmitted to an ERP, DMS, workflow, or other enterprise system.

The entire process takes place within the organization's infrastructure. Documents are not transmitted to public cloud services and remain under the full control of the data owner.

Cloud or on-premise? Evaluating the pros and cons of each approach

CLOUD	ON-PREMISE
Low initial investment	Initial infrastructure investment
Pay-as-you-go AI usage fees (tokens, API)	No recurring fees for AI models*
Leverages the latest cloud LLM models	Model selection based on local infrastructure
Typically higher processing speed	Slightly lower extraction speed depending on the selected model and hardware
Data is processed in a cloud service	Data remains within the organization
Limitations may arise from the organization's security policy	Ideal for regulated organizations and companies with an emphasis on data sensitivity

* Operating costs primarily consist of proprietary infrastructure, its administration, and power consumption.

Cloud AI services are ideal where rapid deployment and maximum performance of state-of-the-art language models are the priority. Conversely, an on-premise solution makes sense for organizations that prioritize data security, long-term operational economics, and full control over their own AI infrastructure.

What is NVIDIA DGX Spark and why it matters

Modern AI no longer needs to run exclusively in data centers or the public cloud. A new generation of AI appliances enables organizations to deploy advanced models directly within their own infrastructure.

This exact principle underpins the on-premise variant of the DocumentExtract solution. It leverages high-performance AI accelerators, such as NVIDIA DGX Spark, which deliver sufficient computing power for automated document data extraction directly on-site. Consequently, organizations can utilize artificial intelligence without the necessity of transmitting documents to the public cloud. At the same time, they acquire infrastructure that can also be leveraged for additional AI use cases.

The solution is well-suited both for proof-of-concept projects and for gradual scaling into larger production environments. Modern AI can thus be operated directly where the most sensitive data is generated and processed.

Single infrastructure, multiple AI use cases

The primary advantage of the on-premise solution extends beyond document extraction alone. The infrastructure utilized for DocumentExtract can subsequently be leveraged for additional AI scenarios across the organization. The identical computing capacity can support internal AI assistants, enterprise knowledge-base chatbots, internal documentation processing, or the deployment of AI agents streamlining targeted business processes.

Consequently, organizations are not merely investing in a tool for processing invoices, contracts, or forms. They are acquiring the foundation for establishing a proprietary AI platform that remains fully under their control and complies with corporate security mandates. From an IT management perspective, this represents an initial step toward broader artificial intelligence adoption without necessitating the migration of sensitive data to the public cloud.

Who is the solution for

The on-premise variant of DocumentExtract is designed primarily for organizations that, for security, legislative, or operational reasons, cannot or do not wish to use public cloud services. Typically, these include government institutions, public sector organizations, and regulated enterprises that need to leverage artificial intelligence while maintaining full control over their data.

FAQ

Must the solution be connected to the internet?

No. The on-premise variant of DocumentExtract can be deployed entirely within the organization’s infrastructure (NVIDIA DGX Spark) without requiring any documents or data to be transmitted to public cloud services.

Does this truly mean that documents never leave the organization?

Yes. In a standard scenario, documents are processed directly within the organization's infrastructure and do not leave its environment. This enables the utilization of artificial intelligence even where security policy or legislation prohibits the use of public cloud services.

What types of documents can DocumentExtract process?

Unlike traditional OCR solutions, DocumentExtract is not restricted to predefined document types. By leveraging modern LLM models, it is capable of processing virtually any document—ranging from invoices and contracts to purchase orders, forms, and technical documentation, as well as industry-specific documents. The key is always selecting the most appropriate AI model for the given scenario and organizational requirements.

Can the solution be integrated with ERP or DMS systems?

Yes. DocumentExtract is designed for seamless integration with enterprise systems such as ERP, DMS, ECM, workflow platforms, or other internal applications. Extracted data can be automatically routed to downstream processes, eliminating the need for manual transcription.

What if document volume or AI requirements increase over time?

The solution is designed to scale alongside the organization's evolving requirements. Operations can begin with a single NVIDIA DGX Spark unit for document extraction, with the infrastructure subsequently expanded through additional units or by transitioning to a higher-performance enterprise architecture. Furthermore, the identical infrastructure can be leveraged concurrently for additional AI use cases.

Can the infrastructure also be utilized for additional AI use cases?

Yes. Alongside automated document extraction, the same infrastructure can also serve enterprise AI assistants, knowledge-base chatbots, internal documentation processing, or the deployment of AI agents automating selected business processes. Consequently, infrastructure investment delivers value far beyond document processing alone.

WOULD YOU LIKE TO LEARN MORE?

Tell us about your situation. Together, we’ll review your requirements, present the options for on-premises AI-powered document mining, and recommend a solution that fits your environment.