Qurait Solutions
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02Service

AI Automation

The step in a process that needs judgement is the one that stays manual. A model can take most of those, if it is wired in properly and knows when to stop.

AThe short version

Workflows that read, decide, and act.

LLM-powered systems that handle documents, route intelligently, and answer over your own knowledge base. Chatbots on your site and on WhatsApp, voice agents on the phone, RAG pipelines behind both.

ChatbotsVoice agentsRAGDocument AI
BSigns this is you

You probably need this if

  • Someone reads every incoming document to work out where it should go.

  • Your team answers the same forty questions, in slightly different words, every week.

  • Useful knowledge lives in PDFs, email threads, and one person's head.

  • Calls go unanswered outside office hours and the enquiry goes somewhere else.

CWhat we build

What the engagement includes

  • Retrieval over your own content

    A pipeline that answers from your documents and cites where the answer came from, rather than from whatever the model half-remembers.

  • Document understanding

    Extraction, classification and routing for invoices, forms, contracts, and the scanned page somebody photographed at an angle.

  • Chatbots

    On your site and on WhatsApp. They hold a real conversation, qualify, and hand over at the point where a person is worth the interruption.

  • Voice agents

    On the phone and in-app, speech to text and back, with barge-in so it can be interrupted the way a person can.

DDeliverables

What you end up holding

  • The pipeline, deployed on your infrastructure or ours
  • An evaluation set, so changes can be measured rather than argued about
  • Cost per conversation, measured rather than estimated
  • A fallback for every path where the model is not confident
EQuestions

Asked often enough to answer here

Will it make things up?
Retrieval and citation are the defence. Answers come from your content and show their source, and anything outside it hands over rather than guesses. We test that with an evaluation set before it goes near a customer.
Which model do you use?
Whichever earns its place on your task and your budget, benchmarked rather than assumed. We also build so the model can be swapped, because the best one changes every few months.
Where does our data go?
Wherever you decide. We can run against a hosted API under a zero-retention agreement, or entirely on infrastructure you control.

Tell us what the work looks like now.

A short conversation is usually enough to say whether this is a week of work or a quarter, and what it would cost.