Bangla and English AI on their own terms
Document, retrieval and language systems designed for Bangla, English and code-switched input instead of treating Bangla as translated English.
When this becomes necessary
A pipeline validated on English is pointed at Bangla text and quietly loses meaning in tokenisation, OCR, spelling variation and mixed-script input. The interface may translate; the system underneath still does not understand the material.
01 — Fit
Who this is for
- Teams whose staff or customers work in Bangla and English
- Archives containing scanned Bangla documents
- Support, education and operations workflows with code-switched text
02 — System
What gets built
- 01Corpus inspection before choosing models or embeddings
- 02Bangla-aware normalisation, tokenisation and OCR handling
- 03Mixed-script retrieval and evaluation questions
- 04Bilingual interfaces that do not hide one language behind a switch
- 05Per-language and per-class quality reporting
03 — Failure boundaries
The safeguards are part of the product.
- Bangla and English are evaluated separately, not averaged together
- OCR failures remain traceable to the source page
- Code-switched input is handled directly rather than routed by guessing a language
- Weak classes are named instead of hidden inside one score
04 — Public proof
What you can inspect before a call.
Nexora AI proves bilingual product delivery on every screen. A public Bangla OCR case study does not exist yet, and this page does not pretend otherwise.
Inspect the proof →Typically 6 to 12 weeks after corpus inspection