Artificial intelligence is useful when it is pointed at one task that costs your people time: answering the same questions every day, reading forms and documents into a system, finding the pattern in a year of data. We build AI around that task, inside the systems you already use, and measure it by the hours it gives back.
We work in Dari, Pashto and English, which matters more here than anywhere: most AI tools were trained mostly on English, and an assistant that cannot read a Pashto message or a Dari invoice is not useful in Afghanistan. Our own product, KankorAsan, runs an AI tutor and explanation engine in Dari and Pashto for students across the country, so this is work we do every day, not a promise.
What we build
Customer and staff assistants
An assistant on your website, in your app or on a messaging channel that answers from your own documents and policies, in the language the customer writes in, and hands over to a person when it should.
Document processing and extraction
Reading IDs, invoices, forms, applications and reports — scanned or photographed — into structured data your system can use, with a person checking the uncertain cases.
Analysis and forecasting
Models that forecast demand, flag unusual transactions, group customers, or score applications, built on your data and explained in plain terms.
Educational and training assistants
Tutors and explanation engines for institutes and training programmes, like the one inside KankorAsan, with limits and content control set by you.
Office automation
The repetitive drafting, summarising, translating and classifying work in an office, done by a tool that your staff review rather than retype.
Responsible deployment
Clear limits on what the system may decide, logging, a human in the loop where the decision matters, and data kept where your policy says it must be.
How an AI project runs
We begin with the task and the data, not the model: what people do today, what a good result looks like, and what it costs when the system is wrong. From there we choose the simplest approach that works — often a well-built search over your documents does more than a chatbot — and prove it on a sample of your real cases before building it out.
Everything ships with an evaluation set, so you can see how often it is right, and with a way to correct it. We support and retrain the system under the agreement that suits you.
Who this is for
- Businesses handling many customer messages or documents a day
- Educational institutions and training programmes
- NGOs with reporting, translation and data-cleaning workloads
- Banks, microfinance and traders with transaction data to understand
- Public bodies processing applications and forms
Questions about applied AI
Does AI work in Dari and Pashto?
Yes, when it is built for it. We choose models and build the surrounding system so that Dari and Pashto are handled properly — script, direction, vocabulary and the Afghan spelling of common terms. Our own product proves it daily.
Where does our data go?
That is agreed in writing. Depending on the project, processing can run on servers you control, on a cloud region of your choice, or on a provider under a data agreement. Nothing leaves your systems without a line in the contract that says so.
What if the AI is wrong?
It will be, sometimes, and the system is designed for that: confidence thresholds, a person reviewing uncertain cases, logs of every answer, and an evaluation set that shows the error rate before and after each change.
Do we need to have data already?
For assistants and document processing, your existing documents and forms are usually enough. For forecasting, a history of a year or more helps; we tell you honestly if there is not enough to build on yet.