TelecomTelenor
Thunder
Product engineering for Telenor Pakistan's Thunder platform — building at telecom scale for a leading mobile operator.
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AI & Data From foundations to production
From data foundations to AI running in production.
AI projects fail for unglamorous reasons — the data was never ready, the use case was not worth building, or nobody could tell whether the output was right. We work the whole chain: the data platform underneath, the models on top, the guardrails around them, and the operations that keep them running. Parts of this we have done for years under other names — predictive maintenance across a national tower network, decision engines at the centre of a digital bank, annotation at production scale. The rest is where the technology has moved, and we have moved with it.
What's included
- AI strategy, use-case discovery & roadmaps
- Generative AI, agents & intelligent automation
- Data platforms, ML and computer vision
- Governance, evaluation & audit trails
Capabilities
Eight ways we put this to work
Each is a service in its own right — start where the value is clearest.
How we work
Start with the decision, not the model
We look for the decision that changes if a prediction is available. If nothing changes, the model is not worth building — and we will say so before you spend on it.
Prove it on real data
A working system on your own data within weeks, with evaluation and human checkpoints from the first iteration rather than bolted on at the end.
Build the foundation as you go
Pipelines, quality and governance get built alongside the use case that needs them, so the second project is cheaper than the first.
Measure against a baseline
We record what the manual process costs before we automate it, so the saving is a measured number rather than a claim.
Hand over, or run it
We harden and operate it around the clock, or hand it to your team with the documentation and playbooks to own it themselves.
What makes this credible
A machine-learning engine forecasting outages, battery performance and fuel across a national tower estate
A six-module decision engine at the centre of a UK digital bank
An annotation operation scaled from 10 to 120 engineers on proven quality
Snowflake, Teradata, Oracle, Microsoft and UiPath partnerships behind the data and automation stack
ISO 27001, 27701 and 9001 certified operations for regulated and public-sector data
Related work
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Let's engineer your next reinvention
Book a no-pressure discovery call. We'll listen, ask the right questions, and come back with a clear plan — usually within 48 hours.