Environmental Sustainability
Software and compute have a real environmental footprint. We are committed to building AI systems that minimise energy consumption, tracking our carbon impact, and continuously reducing it as we scale.
Our Commitment
As a technology company developing AI infrastructure for Pakistan, SBF Consultancy recognises that AI compute is energy-intensive. We hold ourselves accountable to continuous improvement — not perfection. Every architectural decision we make considers the energy cost of the systems we build.
Pak-LLM's design philosophy — efficient tokenisation, quantised models, and lean inference pipelines — is simultaneously good engineering and good environmental practice. We are building a platform that is sustainable by design, not as an afterthought.
Read our sustainability pledge →Our Sustainable Practices
Inference Efficiency by Design
Pak-LLM's custom Urdu tokenizer reduces token count per query by up to 30% compared to standard Western LLM tokenizers. Fewer tokens means fewer compute cycles, lower GPU utilisation, and directly reduced energy consumption per transaction — environmental impact baked into the architecture itself.
Model Quantisation & Distillation
We prioritise efficient model formats and parameter-distilled architectures over bloated legacy models wherever quality targets allow. Leaner models achieve comparable output quality at a fraction of the power draw.
Energy-Efficient Hardware
Our on-premise Karachi Micro-Node hardware is selected for performance-per-watt efficiency. We track PUE (Power Usage Effectiveness) across our compute nodes and target a PUE below 1.5, consistent with modern data centre best practices.
Carbon Footprint Tracking
Starting FY2026, we are tracking and reporting our annual digital carbon footprint using the Green Software Foundation's Software Carbon Intensity (SCI) specification — a transparent, standardised metric for software emissions.
Renewable Energy Roadmap
We are evaluating solar energy procurement for our on-premise compute nodes in Karachi as part of our 2027 infrastructure roadmap. Pakistan receives an average of 7–8 hours of peak sunlight daily — a significant renewable opportunity for our node operations.
Hardware Lifecycle Management
End-of-life compute hardware is disposed of through certified e-waste recycling partners in Karachi. We do not send hardware to landfill. We publish hardware refresh cycles in our annual sustainability update.
Software Carbon Intensity (SCI)
Starting FY2026, we are publishing our SCI score annually — the carbon emitted per unit of functional software output. The SCI specification, maintained by the Green Software Foundation, provides a standardised and comparable metric for software emissions that goes beyond simple energy consumption to account for hardware embodied carbon and usage intensity.
Learn about SCI ↗