Karzaan AI

From smart agents to process automation, we design and build AI around your business

AI

AI that actually gets work done

From smart agents and enterprise chatbots to document processing and forecasting, Karzaan designs AI around your processes and connects it to the software you already use.

Request: “What’s the status of order 4218?”
  1. Understanding the request and the customer’s intent
  2. Searching the CRM and the warehouse system
  3. Writing the reply and logging a follow-up in the CRM
  4. Handing sensitive cases to a human expert
Done, without keeping the customer waiting

Why AI, and why now?

In just a few years, language models and AI tools have gone from lab experiments to practical tools. Today, work such as answering customers’ repetitive questions, reading and sorting documents, summarizing reports or finding one fact among thousands of files can be automated at a fraction of the former time and cost.

But AI only delivers its real value when it is connected to your own data and software. A generic chatbot knows nothing about your customers’ orders, your contracts or your internal policies. That is exactly what we do at Karzaan: build AI that knows your organization, works inside your security boundaries and feeds its output straight into everyday processes.

AI agents

An agent doesn’t just answer; it acts. An AI agent understands the goal, breaks it into smaller steps and uses the right tool for each: querying a database, calling your software’s APIs, drafting an email or building a report. We design agents with a clearly limited scope of access, a full log of every action and a human approval point for sensitive work, so they are both fast and trustworthy.

Example: Karzaan’s LXP is a working example of this approach: 11 agents that together run the learning journey, from getting to know the learner to the final assessment.

AI agents

Where it helps

  • A sales follow-up agent that sorts leads and drafts follow-up messages
  • A reporting agent that gathers data every morning and sends a management summary
  • An operations agent that logs, routes and tracks internal requests
  • Multi-agent systems that work together like a team

Chatbots and support assistants

Where it helps

  • Works on your website, app, Telegram, WhatsApp and local messengers
  • Answers in Persian, Kurdish, Arabic and English
  • Order tracking, appointment booking and request logging without an operator
  • Reports on the most frequent questions to improve products and services
Chatbots and support assistants

Our chatbots don’t run on fixed scripts. They understand questions in natural language, find answers in your own trusted sources (website, product catalogue, sales policies, order history) and, when a topic is beyond them, hand the conversation to a human agent along with a full summary. The result is a lighter load on your support team and faster answers for customers.

Example: An online store where most messages are “where’s my order?” can answer them fully automatically with live order data.
Enterprise knowledge assistant

In most organizations knowledge is scattered across thousands of PDFs, Word files, emails and systems, and finding a simple answer can take hours. With retrieval-augmented generation (RAG), your documents are indexed and the assistant builds its answer only from them and shows the source, so answers can be checked and the model is kept from guessing. Each user’s access level is respected, so people only see documents they are allowed to.

Example: Instead of digging through folders, a new employee asks “what’s the limit for travel expenses?” and gets the answer with the exact clause of the policy.

Enterprise knowledge assistant

Where it helps

  • Answers that cite the source document and page
  • Works with PDF, Word, Excel, web pages and databases
  • Respects users’ access rights to confidential documents
  • Updates itself as new documents are added

Intelligent document processing

Where it helps

  • Reading Persian and Arabic text from images and scans (OCR)
  • Field extraction from invoices, receipts, contracts and admin forms
  • Cross-checking documents and spotting discrepancies
  • Summarizing long contracts and highlighting risky clauses
Intelligent document processing

Typing data from paper and PDFs into software is slow, error-prone and expensive. Our document processing system reads Persian, Arabic and English text even from images and scans, recognizes the document type, extracts key fields such as amount, date, counterparty or invoice number, and sends them to your finance or admin system for approval or direct entry. Suspicious or unreadable items are flagged for human review.

Example: Instead of typing in hundreds of invoices a month, the finance team only reviews and approves what has been extracted.
Data analysis and forecasting

The data that has piled up in your software for years can become better decisions. We use machine learning models to analyze trends, forecast future sales and demand, spot customers at risk of leaving earlier and raise alerts on anomalies. We also build dashboards where a manager can simply ask “which branch’s sales dropped this month, and why?” and see the answer with a chart.

Example: A distribution company can forecast demand per region to avoid stock-outs while reducing capital tied up in the warehouse.

Data analysis and forecasting

Where it helps

  • Sales and demand forecasts for inventory and production planning
  • Identifying customers likely to leave and suggesting what to do
  • Anomaly detection in transactions, costs and system performance
  • Reporting by asking questions in natural language

Persian, Kurdish and Arabic language AI

Where it helps

  • Sentiment analysis and sorting of customer reviews and tickets
  • Speech-to-text and summaries of meetings and calls
  • Translation and localization between Persian, Kurdish, Arabic and English
  • Writing content in your brand’s voice, with human review
Persian, Kurdish and Arabic language AI

Many AI tools are built for English and struggle with Persian, Kurdish or Arabic, with their spacing rules, numerals and local expressions. We tune and evaluate models and pipelines for these languages so the output feels natural and accurate to local users, from analyzing customer comments on social media to transcribing call-centre calls and pulling out their key points.

Example: A call centre can transcribe every call and get a daily report of the most important complaints and requests.
AI for fintech and financial services

Building on Karzaan’s experience with payment and financial systems, we apply AI where it matters most: detecting unusual transaction patterns in real time, making credit scoring more accurate with behavioural data and speeding up identity checks (KYC) by reading documents and matching faces automatically. All of these models are designed to be explainable, so the reason behind each decision is clear to staff and regulators.

Example: A payment gateway can hold high-risk transactions before settlement and send them for review.

AI for fintech and financial services

Where it helps

  • Real-time detection of suspicious transactions and fraud
  • Smarter customer credit scoring
  • Digital identity checks with document reading and face matching
  • Smart assistants for bank and wallet customers

AI built into your existing software

Where it helps

  • Adding a smart assistant to existing admin panels
  • Smart product and content recommendations on your site and app
  • Connecting to cloud models or open-source models on your own servers
  • Workflow automation across different systems
AI built into your existing software

You don’t have to rebuild everything to use AI. Because Karzaan builds enterprise software, LMSs, financial systems and websites, we know where to add AI to an existing system for the biggest return, from smart product recommendations in a store and automatic customer summaries in a CRM to generating quiz questions in an LMS. Connections are made through secure APIs with minimal change to your current system.

Example: An existing learning system can gain automatic quiz and lesson-summary generation without changing its structure.

How does an agent work in practice?

Example: a store’s support agent connected to the order, warehouse and CRM systems.

  1. 1 Message in A customer asks a question or files a complaint on the website or a messenger.
  2. 2 Understand and plan The agent works out the customer’s intent and decides which information and tools it needs.
  3. 3 Act in your systems It reads the order status, checks stock and, if needed, opens a return request.
  4. 4 Human approval Sensitive actions such as refunds go to a staff member for approval before they happen.
  5. 5 Reply and record The customer gets a reply, and the whole conversation and every action are recorded in the CRM.

How we work with you

  1. 1

    Find the opportunities

    In joint sessions we find repetitive, costly processes and prioritize the opportunities with the biggest return.

  2. 2

    Proof of concept

    Within a few weeks we build a working prototype on your real data, so you see results before investing fully.

  3. 3

    Build and integrate

    We build the final solution with security, scalability and full connection to your software.

  4. 4

    Secure deployment

    We deploy on your own servers or a private cloud and train your users.

  5. 5

    Monitor and improve

    We measure answer quality and real impact on the work, and keep improving the system.

Security and data privacy from day one

Data security is organizations’ biggest concern about AI. We design solutions so your data stays under your control.

  • Open-source models can run on your internal servers, with no data leaving the building
  • Fine-grained access levels for users and agents
  • A full log of every question, answer and action for auditing
  • Confidential information filtered out before it reaches any model
  • A human approval point for sensitive decisions and actions

Who is it for?

Banking, fintech and insurance
Education and HR
Retail and e-commerce
Manufacturing and distribution
Healthcare
Government and public services

A working example: an LXP with 11 AI agents

Karzaan’s learning experience platform shows what well-designed agents can do: interviewing the learner, choosing resources, planning, interactive teaching, quizzing, spaced review and supervision, all done by agents working together.

See the LXP and its agents

Frequently asked questions

Will our data be used to train other people’s models?

No. Depending on your needs, we can run models entirely on your internal servers or use services that don’t train on submitted data. Where data is stored and who can access it are agreed clearly before the project starts.

How much data do we need to start?

For chatbots and knowledge assistants, the documents and information you already have are enough. Forecasting models usually need months or years of history; during discovery we check the quality and volume of your data and tell you honestly what is feasible.

Will AI replace our staff?

Our aim is to remove repetitive, low-value work so your people can focus on work that needs human judgement and experience. In our designs, important decisions always have a human approval point.

How long does an AI project take?

A prototype is usually ready within a few weeks. The time for the final version depends on how many systems we need to connect to and how complex the process is; we give you an exact schedule after the discovery stage.

Does AI work well in Persian?

Today’s models handle Persian, Arabic and, to a good extent, Kurdish well, but a professional result needs tuning and evaluation with your business’s data and terminology. That is part of every project we do.

Can you add AI to software built by another company?

In most cases yes, as long as the software has an API or some way to access its data. If it doesn’t, we look at alternative ways to connect and suggest the best one.

Let’s find where AI will make the biggest difference for you

In a free consultation we review your processes and suggest a few specific, practical opportunities to use AI.