Hi Indie Hackers,
I've been deep in the synthetic data space for a while. My previous project was very technical. I've now evolved it into Synthetic-Engine — a purpose-built engine that directly generates complete, photorealistic scene images of business documents.
We’re talking invoices, bank statements, receipts, contracts, delivery notes — whatever you need — generated from scratch with production-level realism. No base image required, no ControlNet-style hallucinations (the classic “text turns into gibberish” problem is basically solved), and the output looks like someone actually printed the document and photographed it in a real environment.
This is the new direction — scene-oriented, highly controllable, and visually convincing enough for serious use cases (VLM/OCR training).
The repo is the best way to evaluate it because one real output image is worth way more than a long description. I’ll keep adding more examples over time as I expand the supported document types and scenes.
I’m currently looking for the right partners — whether that’s teams working on document AI, FinTech/enterprise automation tools, data teams who need clean training data without privacy headaches, or anyone who wants to explore commercial applications or integrations.
If this solves a real pain point for you or your product, I’d love to hear from you.
Check it out here:
https://github.com/alrowilde/synthetic-engine
Thanks!
This is a strong direction — especially moving from “generate text correctly” to “generate scenes that behave like real-world documents.”
Most synthetic doc pipelines fail not at structure, but at realism under OCR/VLM conditions (lighting, distortion, noise, layout edge cases). If you’ve actually stabilized that layer, this becomes immediately useful for production training pipelines.
The interesting unlock here isn’t just generation — it’s building a closed-loop system:
generate → validate (OCR/VLM) → score → regenerate → dataset curation.
That’s where synthetic data becomes a reliable asset instead of just samples.
I’ve been working on similar ML/data pipelines and contributed to open-source tooling around reproducibility + automation — especially integrating generation systems with evaluation and QA layers.
If you’re exploring partnerships or turning this into a production-grade pipeline (dataset generation infra, QA scoring, or integration with doc AI systems), I’d be interested in collaborating on a paid basis.
WhatsApp: +1 (361) 332-6512
Yeah, I built it a few months ago.
Now it's no longer just a script .
I've combined the entire pipeline into a visual interface.
Please feel free to take a look at our showcase! 😊