Projects

Problem: Large number of files without bleeds.

Solution: Script creates bleeds by copying the document edges and scaling them.

Impact: No need to send the file back to the client for correction or manually create bleeds.

Problem: Manual imposition of jobs (e.g., flyers, business cards) is time-consuming.

Solution: The script calculates the number of items on a sheet and performs automatic imposition.

Impact: Imposition time reduced from about 10 min to 10 seconds.

Problem: Manual imposition of booklets or manuals is very time-consuming.

Solution: The script calculates the number of items on a sheet and performs automatic imposition.

Impact: Imposition time reduced from about 20 min to 10 seconds.

Problem: Client sends dozens of PDF files at once, each requiring manual checking before printing.

Solution: A PowerShell script monitors a folder and automatically runs preflight in Adobe Acrobat Pro (via Droplet). Correct files go to the Correct folder, incorrect ones to Incorrect along with a text report describing found issues.

Impact: Elimination of manual file checking — verification of dozens of PDFs happens in the background, without operator intervention.

Problem: Clients often do not understand where the trim size ends, where the bleed begins, and which area should remain safe for important content.

Solution: The script generates a clear project preview with dimensions, safe area/trim/bleed frames, info/warning/danger panels, and an optional right-side bleed cut simulation.

Impact: It makes client communication faster, reduces approval misunderstandings, and helps explain print production rules in a visual way.

Problem: Preparing product photos for online stores, promotional leaflets, or sales platforms requires manually cropping each file individually in Photoshop, which for large batches takes many hours of operator work.

Solution: A Gemini CLI Agent Skill that automatically detects the main object in each image in a folder, calculates its geometry, and calls ImageMagick to precisely crop the file into a square at a given resolution (e.g., 480x480px). Supports batch processing of an entire folder with a single terminal command.

Impact: Cropping hundreds of product photos runs in the background without any operator involvement. Original files remain untouched, and cropped results are automatically saved to a separate folder.

Problem: Manually replacing the FSC mark in a large number of PDF files is time-consuming and error-prone.

Solution: A desktop application automatically detects a target graphic in PDF files and overlays a new asset in the same position in batch mode.

Impact: It reduces manual work in repetitive update tasks and can also be used for other logos or recurring graphic elements.

Problem: Clients often find it difficult to understand how finishes such as spot UV varnish or embossing will look on the final business card, because in production files they are usually shown as black-and-white masks.

Solution: This web application renders PDF files and displays the business card as a 3D object, presenting those finishing effects in a more realistic way using Three.js and PDF.js.

Impact: It makes it easier to show clients the final result before printing, reduces misunderstandings, and helps evaluate the design more quickly.

Problem: Images submitted for printing may have incorrect technical specifications or visual defects, such as blurring, compression artifacts, or signs of artificial upscaling. Manually checking these files is time-consuming.

Solution: An n8n automation first checks image specifications against a JSON file (dimensions, PPI, aspect ratio, and orientation). Images that pass this validation are then sent to Gemini. AI analyzes three crops at their original 1:1 pixel resolution, evaluating 16 quality criteria for the image as a whole. The results of the technical checks and AI analysis are saved in a single JSON report for each image.

Impact: Automates initial image validation and report generation. The project is also experimental, exploring the potential of AI for image quality assessment in DTP workflows. Tests revealed limitations in detecting detail loss caused by upscaling and compression, so AI assessment remains a supporting tool rather than a replacement for professional prepress inspection.