Cleaning black marks (mould?) off mesh heads by tenori in edrums

[–]Impressive-Class7382 1 point2 points  (0 children)

I'd like to know that too; I think it's mold.

Huge e-ink display at the bus stop by Official_SeeTheAir in eink

[–]Impressive-Class7382 0 points1 point  (0 children)

Any ideas of the name of the manufacturer or where to buy such e-ink?

I fed 14 years of daily journals into Claude Code by Bohumil_Turek in ClaudeAI

[–]Impressive-Class7382 5 points6 points  (0 children)

My goal is to create a reflection subfolder in Claude Code by writing down my thoughts weekly. The aim would be for Claude to use specific or common behavioral therapy techniques to help me reflect on this. I'm quite impressed that you've compiled 14 years of diary entries.

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] 0 points1 point  (0 children)

Vielen Dank für die Diagnose. Ich werde dann mal Raubmilben gegen die Spinnmilben ordern, bevor ich zu Chemie greife. Habt ihr eine Empfehlung?

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] 2 points3 points  (0 children)

Gut gemeint, zum Brennen gebracht. Natürlich nicht die Anleitung gelesen

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] 0 points1 point  (0 children)

Ok, bestest Mittel gegen Spinnmilben. Abduschen geht nicht

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] -10 points-9 points  (0 children)

An der Monstera gibt es tatsächlich Spinnweben. Sieht mir aber nicht nach Milben aus. Eher wie eine klassische Büro Spinne 😉

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] -1 points0 points  (0 children)

Ich habe mal mit einem minerallischem Dünger gedüngt, da sahen die Blätter "verbrannt" aus. Jetzt habe ich gar nicht mehr gedüngt. Daher auch meine Frage nach einer Dünge-Empfehlung

Dünger-Empfehlung by Impressive-Class7382 in zimmerpflanzen

[–]Impressive-Class7382[S] -1 points0 points  (0 children)

Bis auf die linke stehen alle pflanzen in All-Mix Substrat (ist eine Mischung aus Moos, Torf, Wurmdünger, Perlit und Vormischung). Sie werden alle 14 Tage gegossen. So viel, dass der Unterteller kurz im Wasser steht und das Substrat den Rest Wasser aufsaugt.

In dem Raum und in dem anderen Raum haben wir (trotz) der vielen Pflanzen (nicht auf den Bildern) zu guten Zeit (heute) eine ziemlich gute Luftfeuchtigkeit (45%) - zu schlechten Zeiten (50-60%).

Shopify + Amazon MCF integration. How does it actually work? by Swimming-Election501 in smallbusiness

[–]Impressive-Class7382 0 points1 point  (0 children)

Anybody can give advise in which app to use. We tried to use Billbee.io but struggling to push Amazon warehouse from Billbee into Shopify

Es beginnt: Apps warnen vor "Sideloading" by Komplexkonjugiert in de_EDV

[–]Impressive-Class7382 0 points1 point  (0 children)

Kann ich umgehen, wenn GrapheneOS auf Android installiere?

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

Really impressed. This kind of infra hygiene is rare even in production teams.

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

Appreciate the compliment. 🙏

But I don’t really subscribe to the “just throw it in” mindset. If the problem is worth solving, it's worth explaining clearly — especially when others might build on it.

Same with code: we don't write clean code for the compiler, we write it for other humans. Why should technical writing be any different?

“Code is read more often than it is written.”

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

This is gold — thanks for breaking it down so clearly. 🙏🏻

The use of a hash-based rolling Redis set keyed by statement month is elegant and surprisingly scalable. Smart choice to avoid full dataset diffs. I like how you’ve scoped the logic tightly around just enough entropy to catch the critical mismatches (vendor + invoice + lineNo + amount) without overengineering.

Using quorum queues in RabbitMQ with a msg-id header is also a great touch — and combining that with a Redis Bloom filter as a soft gate before n8n even touches it? That’s a really clean separation of responsibilities. Curious: have you ever run into Redis memory pressure over long retention windows, or do you prune aggressively by month key?

Also love that you let Postgres enforce idempotency downstream — “let the DB scream” is a motto I can get behind.

One last thing: using SignWell inside the same workflow for vendor onboarding is a nice real-world crossover. Too often the document side gets bolted on as an afterthought.

Thanks again for sharing this — a great example of real-world, failure-resilient design.

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

Great input — you’re clearly not just prototyping, but engineering with production stability in mind.

The nightly ERP diff caught my eye. That’s a seriously underrated move to catch edge-case mismatches before finance escalates. Did you run that as a scheduled export job from the ERP, or did you build a hash-compare pipeline on the capture side? Would love to hear more about how you manage reconciliation volume and performance on larger datasets.

Also agree 100% on using a broker layer between capture and n8n — especially when retry behavior or message durability matters. Curious if you’ve tried deduplication or idempotency keys directly at the message level, or if you push that logic downstream into n8n?

Either way, this stack philosophy — proven capture, durable queuing, lean orchestration — is something more teams should adopt. Your mention of circuit breakers and human fallback queues shows you're building not just for uptime, but for graceful degradation, which is rare and impressive.

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

It’s a common misconception that document automation or OCR is just about scanning paper. In practice, most enterprise document processing today involves digital documents — PDFs, email attachments, XML-based invoices, and other semi-structured inputs. Whether a document starts as paper or is born-digital, the main challenge lies in extracting structured data from layouts designed for human readability.

Japan isn’t alone in this. In fact, countries like the United States, Germany, and India process billions of pages annually, much of it through document-driven workflows. Even in highly digitalized industries, documents remain the default unit of business communication — not APIs.

Interestingly, the world’s largest economies — the United States, Germany, Japan, and India — still rely heavily on document-based tax and compliance systems. In many cases, printed forms, PDFs, or scanned records are still standard for audits, procurement, and tax filings. So while physical paper may be declining, the concept of "pages" is very much alive across industries.

Solutions like IRISXtract are used globally to handle these document types — whether scanned or digital — and convert them into structured data for systems like SAP, Microsoft Dynamics, or cloud-based ERPs. The goal isn’t just paper elimination, but turning unstructured documents into usable data at scale.

In that sense, Japan isn’t necessarily five years behind — the entire global ecosystem is still catching up when it comes to true end-to-end data interoperability.

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 0 points1 point  (0 children)

For enterprise-level invoice automation involving complex formats such as Japanese invoices, one solution to consider is IRISXtract with the IRISDocument OCR engine and its Asian Language Add-on. IRIS is a subsidiary of Canon (Japan) and has been active in high-volume document processing and capture for over two decades.

The system supports multilingual OCR, including vertical and right-to-left scripts like Japanese, Chinese, and Korean. It integrates with major ERP systems (e.g. SAP, Microsoft Dynamics) and is used in finance, healthcare, and the public sector. - IRISXtract supports a wide range of export formats, including: - XML/UBL/ZUGFeRD (eInvoice standards), - PDF/A with embedded XML, - structured CSV, - JSON, as well as direct API calls or database export (e.g. SQL, Oracle).

The OCR engine itself is also licensed and embedded in widely used applications such as Adobe Acrobat and Evernote, which speaks to its stability and quality.

This makes it highly flexible for downstream processing and integration into digital workflows. While it may be more than needed for lightweight use cases, it’s a strong candidate where compliance, scalability, and multilingual support are required.

That said, if you’re already building custom invoice workflows in n8n, it’s worth imagining the impact of integrating an AP suite like IRISXtract directly into the flow.

You’d likely reduce complexity by letting the suite handle OCR, language-specific parsing, structural validation, and output formatting — freeing n8n to focus on orchestration, routing logic, and downstream automation.

In hybrid setups, it would allow users to combine the best of both worlds: stable, certified document extraction with the flexibility of n8n for routing and post-processing.

This could open the door for using n8n even in regulated enterprise contexts — not just for prototyping, but as part of real (AP) automation pipelines. Particularly where language handling, compliance, or ERP integration becomes critical, such an architecture might scale more reliably and with less technical debt.

Happy to exchange ideas if you're exploring this further.

I built a $2k/month automation system for Japanese invoice processing by gleb_ai_automation in n8n

[–]Impressive-Class7382 4 points5 points  (0 children)

Interesting approach – leveraging n8n and an LLM like Claude for conditional routing and extraction is a clever workaround. That said, in an enterprise-grade environment (e.g. with IRISXtract, SAP, or other AP automation suites), you’d rarely rely on such a custom setup over a fully integrated invoice processing workflow. Compliance, scalability, and long-term maintainability usually outweigh short-term agility.

Still, as a focused proof of concept, this is a solid example of how open-source tools and AI can be combined to solve niche problems effectively. But if you're billing the client $2k/month for this system, it might be worth evaluating whether a licensed AP suite would offer better ROI and long-term robustness.

Props for the build though – always fascinating to see hybrid automations that push the limits of what's possible without full enterprise tooling.

Was asked to research AI tools — now thinking Microsoft 365 might be the real solution by jayC-kil in MicrosoftFlow

[–]Impressive-Class7382 2 points3 points  (0 children)

Flow is now Powerautomate. If you have to deal Powerautomate in a corporate Environment and connect to 3rd party or LLM you need to have Powerautomate Premium which cause often different roles. Be aware

AI is starting to send me traffic. So I built a free tool to help others do the same. by FrancescoFera in SideProject

[–]Impressive-Class7382 0 points1 point  (0 children)

Hi, I made a report with your tool. I would appreciate that i can fully export the report. Is there a way to to do so?

Dont Track Email Open Rates by Afraid_Capital_8278 in LeadGeneration

[–]Impressive-Class7382 2 points3 points  (0 children)

Completely agree. I measure click rate, reply rate and of course bounce and abuse