NLP for Urdu and Roman Urdu
Search, message sorting, summaries and replies that cope with English, Urdu in its own script and Urdu typed in Latin letters, often all in the same sentence.
Where English-only software falls short.
- Search that needs perfect spelling The same word is spelled three different ways in Roman Urdu, and a keyword search only finds the one you typed.
- Messages sorted by hand Complaints, orders and sales leads arrive mixed together in one inbox.
- Voice notes nobody has time for Customers and staff send long voice notes that someone has to listen to and type up.
- English-only software Software built for English alone quietly ignores the messages customers find easiest to write.
Language tools that meet customers halfway.
- Meaning-based search Help centres and product catalogues that find the right answer whatever spelling or script is used.
- Message routing WhatsApp and email messages sorted into complaints, orders, prices and leads, then sent to the right person.
- Voice-note transcripts and summaries Urdu voice notes transcribed and summarised in English for the team, with names and amounts checked.
- Feedback and review analysis Reviews and survey answers grouped by topic and tone, so recurring problems stand out.
Building for the way people really write.
- Gather real messages A sample of real customer messages, with personal details removed, so the system meets the spellings and slang it will actually see.
- Define the categories What each message type means for your team and who should receive it.
- Choose the model A hosted or self-hosted language model, chosen by accuracy on your messages, cost and privacy.
- Measure on your data Accuracy per category and per script, including mixed English-Urdu sentences.
- Connect the channels WhatsApp, email, website forms or your CRM, wherever the text arrives.
- Keep a person in the loop Unclear messages go to staff, and their corrections improve the next version.
What the language system delivers.
- Search or routing working on your channels
- Support for English, Urdu and Roman Urdu
- Accuracy report on your own messages
- Review screen for unclear cases
- Dashboard of topics and trends
- Documentation and handover
Questions
Which tasks work best today?
Sorting and routing messages, meaning-based search and short summaries work well. Reading printed Urdu from images and transcribing noisy audio are harder and need checks.
Can it work inside our existing helpdesk or CRM?
Usually, yes. Messages can be read from and written back to most helpdesks and CRMs that have an API.
How is accuracy measured?
On a held-out set of your own messages, per category and per script, so you can see whether Roman Urdu, Urdu or mixed messages are the weak spot.
Does customer text leave our systems?
Only if you choose a hosted model. A self-hosted model keeps all text on your own server, at the cost of running it.