Questions, answered. Security, deployment & pricing.

With a Data Readiness Assessment. We map the process you want to improve, check whether your data can support AI, and size the value in hours and money. Discovery shows the value before anyone pays for a build.

Yes. A proof of concept runs on your own sample data, built to look like your systems. For order intake, for example, we typically use 10 to 15 real, anonymised orders with success measures agreed up front.

A process owner, a handful of real sample documents or records, and access to the people who do the work today. We handle the rest.

Where your data must live: your cloud (AWS, Azure or Google Cloud), your own servers, or fully offline and on-premise. Our engineers can also work on site.

It doesn't have to. Our data agent, for example, runs analysis inside your systems with read-only access, and only aggregated, verified results leave.

Not in our systems unless you want it to. People approve the output: operators approve orders, analysts sign off credit files, reviewers decide medium-risk applications. Nobody is auto-declined.

Figures are computed by deterministic code, not narrated by a model, and every claim links to its source. Where a figure can't be verified, it is flagged for a person instead of guessed.

You pay for time and people. Scope is set in the Data Readiness Assessment, then the right team for an agreed duration — including testing and UAT — gives a clear, itemised quote agreed before we start.

No licence traps and no black-box pricing. You pay for the service you receive.

Yes. Through staff augmentation, vetted engineers from Pakistan's top universities work inside your team across AI/ML, data, cloud, full stack and QA.