Blog
Product updates, engineering deep-dives, and customer stories.
- Product
Welcome to the Docusift blog
What we're building, why template-free extraction matters, and what to expect from this blog going forward.
- Product
Why template-based extraction keeps breaking (and what we did instead)
Templates worked when documents fit a known shape. They stopped working a long time ago. Here's what fails, why, and how Docusift's template-free pipeline routes around it.
- Product
How Docusift keeps your documents isolated
Every workspace gets its own logical storage scope, and Enterprise customers can bring their own bucket. Here is what isolation means in practice — and what it does not mean.
- Product
Extraction confidence isn't accuracy: how to actually use the number
Confidence scores are the most misread number in document AI. Here's what they actually mean, how to set thresholds, and why pinning your accuracy KPI to 'average confidence' will quietly mislead you.
- Product
Migrating from Docparser, Nanonets, or Rossum: a practical guide
If you're running a legacy template-based extractor and considering Docusift, here's the realistic migration path — what to keep, what to throw out, and a one-week plan to validate.
- Engineering
Structured outputs, vision models, and the boring engineering between them
Multimodal AI does the magic. The other 80% of a production extraction pipeline is plumbing. A walkthrough of the parts you do not think about until they break: schema enforcement, retry semantics, idempotency, cost attribution.