Why synthetic metadata matters for LLMs
Exploring how generated labels improve model robustness.
Read →JOLPA LIMITED specialises in curated data feed syndication and synthetic metadata generation. We build the structured datasets that power the next generation of LLMs and computer vision systems.
Initiate data stream →Data pipelines operational. Synthetic generation active. Curated feeds ready for ingestion.
jolpa@data-syndicate:~$ cat company_profile.jol
JOLPA LIMITED bridges the gap between raw digital content and the structured datasets required for AI development. Founded by Jolyon Caryle Palmer, we operate from Southwater, West Sussex, serving AI labs, computer vision startups, and enterprise ML teams across the UK and beyond.
jolpa@data-syndicate:~$ ./list_capabilities --verbose
> Curated data feed syndication
> Synthetic metadata generation (LLM + CV)
> Dataset structuring & enrichment
> Custom annotation pipelines
jolpa@data-syndicate:~$ _
Curated, continuous streams of structured data tailored to your model's domain — finance, legal, medical, and more.
Procedurally generated labels, descriptions, and attributes that augment real-world datasets for robust training.
High‑quality, deduplicated text corpora with rich metadata for pretraining, fine‑tuning, and RLHF.
Synthetic imagery, bounding boxes, segmentation masks, and scene graphs for vision model development.
Petabyte‑ready pipelines
GDPR‑aligned data handling
Tailored to your vertical
Fresh data, always
2.1B token curated dataset for a London‑based legal AI startup.
[legal_v1.4.jol]500k annotated product images for computer vision shelf analysis.
[retail_synth_v2.jol]Real‑time structured news feed for sentiment analysis models.
[news_feed_live.jol]"JOLPA's data feeds transformed our model performance. Clean, consistent, and always on time."
"The synthetic metadata pipeline saved us months of manual annotation. Highly recommended."
"Jolyon and his team understand data at a deep level. A true partner for AI development."
"JOLPA's data feeds transformed our model performance. Clean, consistent, and always on time."
"The synthetic metadata pipeline saved us months of manual annotation. Highly recommended."
"Jolyon and his team understand data at a deep level. A true partner for AI development."
Exploring how generated labels improve model robustness.
Read →Architecture and lessons learned from processing 10k+ sources.
Read →How procedural generation fills gaps in training datasets.
Read →