AI for structuring AIM Electronic’s technical and commercial knowledge.

Process engineering applied to electronics manufacturing.

AIM Electronic is a Spanish company founded in 2008 that represents and supplies machinery and consumables from international manufacturers to the electronics industry in Spain and Portugal.

Its work goes beyond selling or installing equipment. AIM advises on machinery, processes, and consumables and provides training and technical support. Its value proposition relies especially on the knowledge of its engineers and process specialists.

Its offering includes AOI and SPI inspection, laser marking, printing, handling, ovens, soldering, cleaning, coating, dispensing, depaneling, prototyping, and consumables such as solder paste, wire, tin bars, and cleaning products.

The end customer

AIM’s customer is not looking for an isolated product reference. It is an industrial company that needs to configure, expand, or optimize an electronics-manufacturing process. The decision may depend on the product, volume, product variety, cycle time, materials, traceability, and defects that must be prevented.

Make existing technical knowledge more accessible.

AIM has a solid foundation of documentation, manufacturer knowledge, and experience accumulated by its specialists. The breadth of its offering means that this information naturally resides across different specialized sources.

The project was not created to correct a lack of organization. It reflects a decision to pursue continuous improvement: locate, connect, and apply knowledge more consistently while preserving traceability and specialist responsibility.

AIM wants to strengthen its internal processes so it can continue to provide rigorous technical support and demonstrate to customers that it is prepared to adopt AI in a useful, responsible way.

• Improve access to approved technical documentation.
• Keep information provenance visible.
• Standardize the minimum structure of inquiries.
• Preserve context throughout the commercial journey.
• Turn corrections and lessons into reusable knowledge.

A strong technical foundation prepared to scale.

AIM already had a catalog, product pages, technical data sheets, manufacturer documentation, and specialists experienced in production engineering, application, and support.

An inquiry may begin with a process need—reducing defects, improving inspection, adjusting a profile, increasing traceability, or selecting a consumable—rather than a specific product reference. To respond, the specialist must connect the application to actual manufacturing conditions.

The first phase was designed to make that connection more accessible and reviewable while respecting existing tools and responsibilities.

Structure knowledge before increasing autonomy.

E2M analyzed which questions specialists receive, what information they need, which sources may be used, and which decisions must remain subject to professional validation.

The decision was to begin with an assisted workflow. AI would prepare a technical-commercial file containing context, sources, confirmed data, and open questions. AIM would retain technical selection, process parameters, and every customer commitment.

A shared file for understanding, consulting, and deciding.

A clear initial scope

Solder paste provides a clear area in which to validate the method: selection may depend on alloy, particle size, application, and process profile. The model can later expand to more complex areas such as AOI and SPI inspection.