data · open source
OCR & Handwriting Recognition with PostgreSQL
OCR & Handwriting Recognition built on PostgreSQL, chosen where it genuinely fits, and swapped where it does not.
- Category
- data
- Vendor
- Open source
- Alternatives we also use
- 6
Why PostgreSQL for this
Pre-processing decides OCR accuracy more than the recognition engine does. Deskew, denoise and contrast correction are where the quality is won.
PostgreSQL is strongest at it handles far more workload than teams expect, with one operational model. For ocr & handwriting recognition that matters because the failure modes of this kind of system tend to cluster exactly there.
The honest trade-off: genuine analytical workloads past a certain scale belong in a warehouse. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. Every engagement opens with a measurement: the cycle time, the cost per transaction, or the error rate we are being asked to move.
Six weeks to something running in production, not six quarters to a strategy document.
The honest assessment
- What it is
- Our default database, relational, JSON, full-text and vector in one engine.
- Strongest at
- it handles far more workload than teams expect, with one operational model
- Trade-off
- genuine analytical workloads past a certain scale belong in a warehouse
- Category
- data
We are not a reseller for PostgreSQL and hold no commission on this choice. Where a different option fits your workload better, the recommendation will say so. That is the entire value of asking us.
What is included
- Pre-processing for skew, noise and poor contrast
- Multi-script recognition including Indian languages
- Table and layout structure preserved, not flattened
- Per-field confidence with a human review queue
- Searchable archive output with the original attached
- Accuracy measured on a sample you verify yourself
Questions
Does it handle Indian languages?
Yes, Devanagari, Tamil, Telugu, Kannada, Malayalam, Bengali, Gujarati, Punjabi and Odia among others. Accuracy varies by script and scan quality, and we measure it on your material rather than quoting a brochure figure.
How accurate is handwriting recognition?
Highly variable. Neat, consistent handwriting reads well; mixed or cursive is much harder. We run a sample first and tell you honestly whether it is viable.
Can you process our physical archive?
Yes, working with scanning partners for the physical capture and handling the digitisation and structuring end.
Alternatives for ocr & handwriting recognition
Same capability, different stack. Each page states its own trade-off.
Building with PostgreSQL?
Bring us the workload and we will tell you whether this is the right stack for it.
Or email bd@dtrasglobal.com · call +91 74118 77878