FAQ

SALTIR develops and integrates custom AI solutions for businesses, focusing on Generative AI, Computer Vision, and AI Literacy—including semantic interoperability. We empower organizations to leverage open-source technologies for secure, independent, and scalable digital transformation.

Open-source AI offers several key benefits:

• Independence & Security: You avoid vendor lock-in and retain full control over your data and infrastructure. Open-source models can be run locally, minimizing the risk of data leakage to third parties.

• Cost-Effectiveness: There are no licensing fees, and you can adapt the technology to your needs, reducing long-term costs.

• Transparency & Trust: The source code is auditable, which increases transparency and allows you to address ethical or security concerns directly.

• Community & Innovation: Open-source solutions benefit from a global community, resulting in rapid innovation, regular updates, and more robust, peer-reviewed technology.

• Customization: You can tailor models and tools to your specific business requirements, ensuring a perfect fit for your use case.

We work with leading open-source frameworks and tools, including:

• Generative AI: Transformer-based Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and frameworks like LLamaIndex, LangChain and N8N for connecting LLMs with external data sources.

• Computer Vision: Deep Learning models, especially Convolutional Neural Networks (CNNs) for image and video analysis, real-time object detection (e.g., YOLO, RF-DETR), and transfer learning for rapid deployment.

• Semantic Interoperability: Ontology-based data integration, middleware for system compatibility, and industry standards (e.g., RDF, JSON-LD) to harmonize data from diverse sources.

Start small and focused:

• Identify a clear use case: Analyze your business and pinpoint a process or challenge where AI can deliver measurable value.

• Pilot project: Begin with a manageable pilot to test the technology and gather insights before scaling up.

• Measure results: Use KPIs aligned with your business goals to evaluate success and refine your approach.

• Scale gradually: Once the pilot proves successful, expand to more complex or holistic processes.

This approach minimizes risk, ensures early wins, and builds internal confidence in AI adoption.

Successful AI projects depend on the knowledge and engagement of your team:

• Domain expertise: Employees understand your business processes and can help define relevant use cases and data requirements.

• Change management: Involving staff reduces resistance, demystifies AI, and ensures the technology is seen as a tool for empowerment, not replacement.

• Continuous improvement: Ongoing feedback from users and experts leads to better, more practical solutions.

We recommend making AI a collaborative effort from the start, involving all relevant stakeholders.

Semantic interoperability means your systems—and AI agents—can exchange and understand data in a unified, meaningful way, regardless of source or format. This enables:

• Seamless data integration: Combining information from different platforms and departments.

• Better decision-making: AI can reason over diverse datasets, providing deeper insights.

• Future-proofing: As your business grows, interoperable data ensures you can adopt new technologies without costly rework.

SALTIR helps you assess your data landscape, improve data quality, and implement standards for semantic interoperability.

Good data is the foundation of every AI project:

• Assess what you have: Inventory your data sources and formats.

• Check quality: Ensure data is accurate, complete, and consistent.

• Identify gaps: Determine what’s missing for your target use case.

• Prepare and clean: Remove duplicates, correct errors, and structure data for analysis.

SALTIR offers AI Literacy services to help you understand, prepare, and optimize your data for successful AI deployment.

We prioritize your data sovereignty:

• On-premise and private cloud options: Keep sensitive data within your infrastructure.

• Open-source transparency: Full visibility into how your data is processed—no hidden algorithms or third-party access.

• Compliance: We help you align with industry standards and regulations.

Timelines vary depending on complexity, but a typical pilot project can be up and running within a few weeks to a few months. Larger, holistic solutions may take longer, but starting small ensures faster returns and lower risk.

Yes. We offer support, maintenance, and training for your team to ensure sustainable AI adoption. Our goal is to empower your organization to use, adapt, and extend AI solutions independently over time.

If you have further questions or want to discuss your specific needs, contact us for a personal consultation.