ESG & Sustainability Policy

1. Why this matters

Most of the AI industry is racing in the opposite direction. Frontier models are bigger, hungrier, and thirstier every quarter — measured in megawatt-hours of training compute, gigalitres of cooling water, and a growing share of national electricity grids. We think that trade-off is unnecessary for the work most organisations actually need AI to do.

Blankstate’s architecture is deliberately the opposite of frontier-scale. Our measurement engine is a small, proprietary, deterministic system that runs on modest compute, without the third-party LLM and model providers that dominate the rest of the industry’s stack. The environmental footprint of running Blankstate is materially lower than the footprint of running a comparable workload through a chain of frontier-model providers — and we treat that as both a moral and a commercial advantage.

This policy sets out the commitments behind that posture: environmental, social, and governance.

2. The shape of the footprint

The graphic below is an order-of-magnitude comparison between a typical frontier-LLM-mediated workload (per measurement) and a typical Blankstate measurement on the same input. The intent is direction, not precision; specific figures depend on the model called, the region, and the workload. The architectural shape, however, is structural — it does not change run-to-run.

3. Environmental commitments

3.1 Low-compute architecture

• The Blankstate measurement engine is proprietary, deterministic, and small. A typical measurement runs in milliseconds on commodity compute — orders of magnitude less energy than an equivalent call to a frontier large language model.
• We do not route customer data through third-party generative model providers in the production data path; we therefore avoid the upstream energy and water cost of that inference.
• New features are reviewed for compute efficiency alongside functional and security requirements; we prefer designs that reduce per-request compute.

3.2 Low water consumption

• Frontier-model inference and training drive significant data-centre cooling water consumption. Because our architecture does not rely on frontier-model inference, our per-request water footprint is materially below the prevailing industry norm.
• We select our hosting regions partly on cooling-water intensity and water-replenishment commitments by the underlying cloud operator, in addition to the legal data-residency requirements our customers contract for.
• We do not run on-premises data-centre cooling.

3.3 Sustainable cloud sourcing

• Our production cloud operator is selected, among other criteria, on the published sustainability commitments of its infrastructure: 100% renewable-energy matching at organisation level, a public 24/7 carbon-free energy target, transparent regional carbon-intensity reporting, and a published water-replenishment commitment.
• We track our cloud operator’s progress against those targets and report it alongside our own metrics.
• We minimise idle compute through right-sized instances, autoscaling, and routine review of unused resources (per BKS-AM-001).
• We prefer regional storage and avoid duplicative cross-region replication where customer data-residency commitments do not require it.

3.4 Federate-when-local principle

We treat each measurement as belonging to the smallest sufficient compute envelope:

• Where measurement can lawfully and effectively run on the user’s own device or the customer’s own infrastructure, it should — eliminating the network leg, the cloud leg, and the marginal cooling-water cost. The deterministic, small-footprint shape of our engine is what makes this possible at all.
• Where measurement must run server-side, it runs at the nearest viable region — keeping inference inside the operational and legal boundary of the customer.
• Federation, not centralisation. Designs that compound population insight without compounding compute are preferred. Coverage scales by adding nodes, not by adding load.

This principle is encoded in product design reviews and is the architectural reason our energy and water curves do not grow with usage in the way frontier-stack architectures do.

3.5 Hardware and devices

• We minimise the hardware footprint of the team — predominantly remote-working personnel using a small, long-life laptop fleet. We do not operate an office data centre.
• Endpoints are kept in service for their full supported life; end-of-life devices are recycled through certified e-waste channels and storage is securely wiped per BKS-AM-001 §10.

3.6 Travel

• Default to remote / asynchronous work; in-person travel is purposeful (customer engagements, regulated workshops, team off-sites) rather than routine.
• We prefer rail over short-haul flight where journey time and cost permit.
• Material travel is reviewed quarterly.

3.7 Measurement and reporting

• We track and report annually: estimated GHG emissions (Scope 1, 2 market-based and location-based, and material Scope 3 categories — purchased goods & services, business travel, employee commuting where remote allowance is provided), production cloud spend as a proxy for compute energy, and counts of issued / decommissioned hardware.
• As we grow we will commit to a science-aligned reduction trajectory and publish progress through the Trust Center.

3.8 Climate-aware roadmap

• Product roadmap decisions are reviewed for compute and inference-cost implications; energy- and water-intensive architectures are not adopted by default.
• We will not introduce third-party generative-model dependencies into the production data path without explicit executive approval and a documented environmental impact assessment.

4. Social commitments

4.1 People

• We are an equal-opportunity employer (see §6 below and BKS-HRS-001).
• We pay personnel fairly for the work and the market, including through the use of independent salary benchmarks.
• We support flexible and remote-first working, with explicit recognition of personnel obligations outside work.
• We provide a safe, respectful, and inclusive workplace (BKS-COC-001).

4.2 Modern slavery and supply chain

• We have a zero-tolerance approach to slavery, servitude, forced labour, and human trafficking in our operations and our supply chain.
• We expect our material suppliers and sub-processors to maintain equivalent commitments and we assess this as part of BKS-TPR-001.
• Our voluntary statement is published as BKS-MSS-001 (Modern Slavery Statement).

4.3 Community and customers

• We bring deterministic, auditable measurement to AI — a public good that supports regulators, auditors, civil-society groups, and the people whose lives are increasingly shaped by AI systems.
• We engage with relevant standards (ISO/IEC 42001, ISO/IEC 27001, NIST AI RMF, the EU AI Act, the UK government’s emerging AI assurance ecosystem) and contribute where invited.

5. Governance commitments

5.1 Information security and privacy

• We protect customer and personnel data through the controls in BKS-ISP-001, BKS-DPP-001, and the wider InfoSec corpus.
• Our zero-personal-data-retention architecture in the measurement path is a privacy-by-design choice — explicitly avoiding the accumulation of personal data as a default. The only personal data persisted by the platform is what is structurally necessary to operate it (sign-in identifiers and user-profile records for authenticated platform users).

5.2 Responsible AI

• We measure AI, we don’t generate it. Our principles are in BKS-AI-001 (Responsible AI & AI Governance Policy).
• We do not use customer data to train or fine-tune models without explicit customer consent.

5.3 Ethical business

• We comply with applicable anti-bribery and anti-corruption law (BKS-ABC-001).
• We comply with applicable sanctions and trade-compliance law (BKS-SAN-001).
• Our conduct standards are in BKS-COC-001.
• We maintain a Speak-Up channel for concerns (BKS-WHB-001).

5.4 Tax

• We pay tax in the jurisdictions where economic activity occurs, in compliance with applicable law and the spirit of that law.
• We do not use artificial structures to reduce tax below the level required by the substance of the activity.

5.5 Board and accountability

• ESG matters are owned at co-founder level.
• Material ESG commitments and progress are reviewed annually and published through the Trust Center.

6. Diversity, equity, and inclusion

Blankstate is committed to building a diverse team and an inclusive workplace.

• Recruitment is based on relevant skill, judgement, and potential. We use structured interviews and consistent assessment criteria.
• We do not discriminate on the basis of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, sexual orientation, nationality, or any other protected characteristic (UK Equality Act 2010; equivalents abroad).
• We support flexible and remote-first working that broadens the talent pool.
• Harassment, bullying, and discrimination are prohibited and treated as gross misconduct (BKS-COC-001 §5; BKS-HRS-001 §8).
• We measure and report the demographics of our team annually, recognising that small absolute numbers require care in disclosure to protect individual privacy.

7. Targets and roadmap

Initial commitments (subject to refinement as we publish baseline measurement):

• Cloud region: maintain a single primary production region for European customers chosen for low water intensity and required data residency.
• Architecture: maintain the no-third-party-LLM-in-the-data-path posture as a public commitment — change requires executive approval and customer notification.
• Federate-when-local: advance the share of measurements that can lawfully and effectively run on-device or on-customer-premises, removing the cloud leg entirely from those workloads.
• Inference efficiency: improve median per-measurement compute year-over-year (specific target to be published once baseline is set).
• Standards: progress towards ISO/IEC 27001 certification (already aligned), ISO/IEC 42001 AIMS adoption, and (when proportionate) B Corp or equivalent third-party verification of social and environmental performance.
• Transparency: annual ESG update published through the Trust Center.

8. Reporting

The ESG owner reports annually on:

• Environmental baseline and progress.
• Social and DEI baseline and progress.
• Governance commitments, audits, and material exceptions.
• Material risks and forward commitments.

9. Approval and review

This policy is approved by Blankstate’s executive ownership and reviewed annually. The current version is published at the Blankstate Trust Center.