Sales prediction
Forecasting from your own history, used for inventory, cash planning and marketing timing.
Transpose Group builds software and infrastructure for organisations in Lebanon and the region. The two divisions share a standard of execution and not much else, which is deliberate.

We deliver personalised solutions scoped to what a client actually needs and can spend, rather than fitting every engagement to the same package. Our research work keeps us current on machine learning, language models and the rest of it, which matters mostly because it lets us tell you when those tools are the wrong answer.
On the technology side the concentration is machine learning sales prediction and intelligent applications, alongside the mobile, web and search work that most businesses need first. On the engineering side it is cathodic protection and the construction, energy and maintenance work around it.
Forecasting from your own history, used for inventory, cash planning and marketing timing.
Software that learns from the data it produces and automates the decisions that are routine.
Applications and sites built cross-platform, mobile-first, and supported after launch.
Technical fixes, keyword work and content that earn ranking rather than rent it.
Corrosion control for pipelines, tanks and buried or submerged structures, design through to monitoring.
Civil, electrical and MEP works, solar systems, and the maintenance that follows them.
It uses your past sales, market trends and customer behaviour to forecast what is coming. Businesses use it to hold the right amount of stock, plan cash with fewer surprises and time marketing spend against actual demand.
Standard development builds defined functionality that behaves the same way every time. Intelligent applications observe how people use them and adapt, and use language models for the parts involving reading or writing text. The second costs more and is only worth it when adaptation or language is where the value sits.
A focused app with a clear scope is typically four to six weeks. Anything involving machine learning, complex integration or regulated data runs into months. We give a timeline once we understand the scope, not before.
Usually, yes, though the honest answer depends on the site. We start with an audit that tells you what is holding it back. Occasionally the finding is that the site needs rebuilding before optimisation is worth the spend.
Both. Scope and budget are set per engagement rather than by a fixed package, and a small well-defined project is often more useful than a large vague one.
Yes. Maintenance, fixes and enhancements are part of how we work. If you would rather run it in-house, the handover includes what your team needs to do that.
Email us a description of the problem. We will tell you whether it is something we should take on, and what the first step would cost.
Describe what is not working and we will tell you what it would take to fix.
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