Languages Supported

Nanonets supports character/word recognition in over 40+ languages including but not limited to:

  1. Afrikaans
  2. Albanian
  3. Arabic
  4. Armenian
  5. Belarusian
  6. Bengali
  7. Bulgarian
  8. Catalan
  9. Chinese
  10. Croatian
  11. Czech
  12. Danish
  13. Dutch
  14. English
  15. Estonian
  16. Filipino
  17. Finnish
  18. French
  19. German
  20. Greek
  21. Gujarati
  22. Hebrew
  23. Hindi
  24. Hungarian
  25. Icelandic
  26. Indonesian
  27. Italian
  28. Japanese
  29. Kannada
  30. Khmer
  31. Korean
  32. Lao
  33. Latvian
  34. Lithuanian
  35. Macedonian
  36. Malay
  37. Malayalam
  38. Marathi
  39. Nepali
  40. Norwegian
  41. Persian
  42. Polish
  43. Portuguese
  44. Punjabi
  45. Romanian
  46. Russian
  47. Russian
  48. Serbian
  49. Serbian
  50. Slovak
  51. Slovenian
  52. Spanish
  53. Swedish
  54. Tagalog
  55. Tamil
  56. Telugu
  57. Thai
  58. Turkish
  59. Ukrainian
  60. Vietnamese
  61. Yiddish
  62. Amharic
  63. Ancient Greek
  64. Assamese
  65. Azerbaijani
  66. Azerbaijani
  67. Basque
  68. Bosnian
  69. Burmese
  70. Cebuano
  71. Cherokee
  72. Dhivehi
  73. Dzonkha
  74. Esperanto
  75. Galician
  76. Georgian
  77. Haitian Creole
  78. Irish
  79. Javanese
  80. Kazakh
  81. Kirghiz
  82. Latin
  83. Maltese
  84. Mongolian
  85. Oriya
  86. Pashto
  87. Sanskrit
  88. Sinhala
  89. Swahili
  90. Syriac
  91. Tibetan
  92. Tigirinya
  93. Urdu
  94. Uzbek
  95. Uzbek
  96. Welsh
  97. Zulu
  98. Acehnese
  99. Acholi
  100. Adangme
  101. Akan
  102. Algonquinian
  103. Araucanian/Mapuche
  104. Asturian
  105. Athabaskan
  106. Aymara
  107. Balinese
  108. Bambara
  109. Bantu
  110. Bashkir
  111. Batak
  112. Bemba
  113. Bikol
  114. Bislama
  115. Breton
  116. Chechen
  117. Chinese (Mandarin, Simplified,)
  118. Chinese (Mandarin, Traditional)
  119. Chinese (Mandarin, Hong Kong)
  120. Choctaw
  121. Chuvash
  122. Cree
  123. Creek
  124. Crimean Tatar
  125. Dakota
  126. Duala
  127. Efik
  128. English (British)
  129. Ewe
  130. Faroese
  131. Fijian
  132. Fon
  133. French (Canadian)
  134. Fulah
  135. Ga
  136. Ganda
  137. Gayo
  138. Gilbertese
  139. Gothic
  140. Guarani
  141. Hausa
  142. Hawaiian
  143. Herero
  144. Hiligaynon
  145. Iban
  146. Igbo
  147. Iloko
  148. Kabyle
  149. Kachin
  150. Kalaallisut
  151. Kamba
  152. Kanuri
  153. Kara-Kalpak
  154. Khasi
  155. Kikuyu
  156. Kinyarwanda
  157. Komi
  158. Kongo
  159. Kosraean
  160. Kuanyama
  161. Lingala
  162. Low German
  163. Lozi
  164. Luba-Katanga
  165. Luo
  166. Madurese
  167. Malagasy
  168. Mandingo
  169. Manx
  170. Maori
  171. Marshallese
  172. Mende
  173. Middle English
  174. Middle High German
  175. Minangkabau
  176. Mohawk
  177. Mongo
  178. Nahuatl
  179. Navajo
  180. Ndonga
  181. Niuean
  182. North Ndebele
  183. Northern Sotho
  184. Nyanja
  185. Nyankole
  186. Nyasa Tonga
  187. Nzima
  188. Occitan
  189. Ojibwa
  190. Old English
  191. Old French
  192. Old High German
  193. Old Norse
  194. Old Provencal
  195. Ossetic
  196. Pampanga
  197. Pangasinan
  198. Papiamento
  199. Portuguese (European)
  200. Quechua
  201. Romansh
  202. Romany
  203. Rundi
  204. Sakha
  205. Samoan
  206. Sango
  207. Scots
  208. Scottish Gaelic
  209. Shona
  210. Songhai
  211. Southern Sotho
  212. Spanish (Latin American)
  213. Sundanese
  214. Swati
  215. Tahitian
  216. Tajik
  217. Tatar
  218. Temne
  219. Tongan
  220. Tsonga
  221. Tswana
  222. Turkmen
  223. Udmurt
  224. Venda
  225. Votic
  226. Western Frisian
  227. Wolof
  228. Xhosa
  229. Yoruba
  230. Zapotec

Can a single model support multiple different languages?

Yes. You can build a single model to handle documents in multiple languages. It contributes to better accuracy and is easy to deploy.

Is handwritten text supported?

Yes, we support handwritten documents — with some important notes:

  • Handwriting must be legible to the human eye. If a human reader struggles to understand the handwriting, AI models may also have difficulty extracting text reliably
  • Results may vary depending on writing style, image clarity, and document structure
  • We recommend testing a few samples to evaluate performance for your specific use case

Tip: Neat, well-scanned handwritten forms (e.g., block letters or clearly written fields) tend to produce better results