Research-Backed Implementation
We do not just "build". We validate. Our delivery models are rooted in rigorous academic and industrial research methods to ensure efficacy and reduce waste.
Our Approach
"Research-backed implementation" means that every technical decision is preceded by evidence gathering. We apply mixed-methods research (quantitative data analysis + qualitative user research) to define the problem space before writing a single line of code. This aligns perfectly with the GDS Discovery phase but adds a layer of academic rigour to the validation process.
Tesseract Foundational Research
Our self-funded research programme: open standards, evidence bases and reference implementations built on public data, published in full for independent verification and reuse. Each project ships with a complete write-up covering challenge, intervention, assurance and reusable assets.
The Challenge
The UK is rolling out continuous water-quality monitoring on wastewater assets under the Environment Act 2021, and the Environment Agency is exploring whether that data can serve as a regulatory tool. The binding question is data quality: calibration drift, fouled probes, telemetry gaps and transcription errors all masquerade as real signals.
The Outcome
The data is complete and internally consistent (COD ≥ BOD holds on every one of 1,382 rows), yet the battery still surfaces multi-year baseline drift and dozens of statistical outliers per determinand. The SHACL rules reject every physically impossible record and pass every clean one, making the trust verdict auditable.
The Challenge
Most of the UK's heritage is digitised but not computable. Aerial photography collections holding tens of millions of frames are scanned, catalogued and mapped, yet a researcher cannot query them at scale by space and time or cross-reference them to other archives. This is the gap the Towards a National Collection programme (AHRC / UKRI) and its N-RICH work set out to close.
The Outcome
Measured finding: the collection is far closer to computation-ready than assumed. 100 percent of records already carry a machine-readable footprint and an ISO-8601 date; the one genuine gap is machine-readable rights. The same standard was then applied unchanged to two further national collections (NAPL Canada and WHAIFinder USA), each lifting to the identical NAPH Baseline at zero SHACL violations, with each collection missing a different Baseline field. The records export cleanly to STAC 1.0, GeoJSON and IIIF, and NAPH publishes the previously unoccupied RiC-O to STAC crosswalk that binds archival provenance to spatiotemporal computability.
The Challenge
Agri-environment schemes are the largest source of government funding for the rural historic environment, yet the wider co-benefits of heritage actions, for nature and for people, are real but evidentially fragmented. As nature recovery is delivered faster and under tighter budgets, heritage actions risk being overlooked unless that value can be evidenced.
The Outcome
A published, replicable protocol, an evidence-map and gap framework, and a real spatial analysis showing 84% of monuments at risk are on farmland, where heritage actions act. Together they make the case that heritage actions deliver multi-objective value, for nature and for people, in a form that withstands scrutiny.
The Challenge
The UK Defence Investment Plan (June 2026) commits over £5bn to autonomous systems and £7.5bn to a Digital Backbone and Digital Targeting Web, all of which depend on heterogeneous systems and allies sharing data a machine can reason over. On the UK side that vocabulary is the Information Exchange Standard (IES); the built environment runs on HQDM and the National Digital Twin. Both are 4D and share a common heritage, yet no machine-readable crosswalk between them had ever been published.
The Outcome
A shared starting point the field lacked, released so suppliers building across defence and built-environment data can start from something concrete. The divergences record names the traps, including the ies:Event to hqdm:event false friend, that a naive label-based mapping would fall into.
The Challenge
PYRAMID (UK Defence Standard 00-134) is the MOD open reference architecture for avionics and mission systems. By design it has no shared data model: its Technical Standard states that components "do not share interface definitions", so a deployment "will use bridges to close the semantic gap", and the accompanying MOD assessment confirms "the PRA does not define a data architecture". The meaning of data across components is left to bridges that are, today, hand-built per deployment.
The Outcome
A shared meaning layer beneath an open avionics architecture, demonstrated on the public standard. No published work grounds PYRAMID, or the related FACE Shared Data Model, in any upper ontology; this occupies that gap with ontologies the UK government already owns.
The Challenge
Scientific data is widely described as FAIR (Findable, Accessible, Interoperable, Reusable), but the claim is rarely tested at scale against a machine-checkable contract, and "AI-ready" is asserted more often than it is evidenced. Without a measurable baseline, funders and repositories cannot see where the real gap is.
The Outcome
The datasets are overwhelmingly findable and accessible, but 0% are interoperable or AI-ready: 100% lack a machine-readable schema, checksums and provenance. The finding names the real gap precisely, and the paired ontology models the AI-ready layer that closes it.
The Challenge
Policy on the security of connective products (IoT, operational technology, computing devices, networking equipment, and software and firmware) is set against headline incident numbers that cannot be reconciled: no shared denominator, non-additive definitions, and vendor telemetry that is never quantified. The field lacks an honest, machine-readable baseline.
The Outcome
A shared, honest baseline that maps real incidents to product class, vector and impact, and states its own limits. It gives policy work something concrete to build on instead of irreconcilable headline figures.
The Challenge
In January 2026 the UK Government published its National Security Assessment on global biodiversity loss, ecosystem collapse and national security, assessing with high confidence that six strategic ecosystems are on a pathway to collapse with security consequences. The assessment is a one-off written document: it ships no machine-readable dataset, no shared ontology and no standing monitoring mechanism, so its cascade chains cannot be queried, versioned or stress-tested.
The Outcome
A first, correctable occupation of a genuine whitespace: the framing is government-endorsed and the science exists (IPBES Nexus 2024), but no open, computation-ready ontology and evidence base of nature-to-security cascades existed. The three government functions map to concrete methods: assess (a nature-security exposure profile binding open indicators to transmission channels), monitor (early-warning statistics including critical slowing down), and mitigate (typed intervention points per cascade, mapped to National Risk Register, IPBES and Kunming-Montreal levers).
Commissioned delivery case studies
Contracts commissioned by government and government-funded programmes, each with a full write-up: challenge, intervention, assurance and reusable assets.
Selected Publications & Talks
Welsh Government Land Valuation Research Report (opens in new tab)
Commissioned by Welsh Government, 2025–2026
Independent research into the feasibility of land value tax models for Wales. Combined statistical analysis of land registry data with international comparator evidence and stakeholder interviews across Welsh local authorities. Findings presented to Welsh Government officials and cited in Senedd committee proceedings.
What Adult Skills Reveal About Social Mobility That Qualifications Hide (opens in new tab)
Open research, OECD Survey of Adult Skills (PIAAC) public-use data, 2026
A reproducible analysis of educational and skills mobility in England using open OECD PIAAC data. Among adults with the same qualification, those from a higher-educated background score about 37 points higher in numeracy, so qualifications understate the advantage of social origin. The data harmonisation is published as an open, machine-readable scheme.
AI Skills for the UK Workforce - Skills England (opens in new tab)
Skills England / UK Government Publication, 2025
Tesseract Academy is cited as an AI training provider and consultancy in Skills England's official research into AI skills for the UK workforce. The publication's methodology included stakeholder workshops with 43 organisations, with Tesseract Academy contributing alongside institutions including The Alan Turing Institute and the Surrey AI Centre.
Proving the Utility of Large Language Models in Cybersecurity Simulations
Collaboration with The Alan Turing Institute, 2025
Research paper exploring how Large Language Models can bolster cybersecurity simulations by automating the creation of synthetic environments and identifying latent vulnerabilities. Co-authored with researchers from The Alan Turing Institute.
Read the paper (PDF) (opens in new tab)Is Blockchain Part of the Future of Art? (opens in new tab)
Journal of the British Blockchain Association (JBBA), Peer-Reviewed
Peer-reviewed research exploring the intersection of distributed ledger technology and the creative industries. Examined provenance tracking, digital ownership, and the implications of blockchain for cultural asset management and intellectual property governance.
FCA Consultation: Stablecoins and UK Crypto Regulation (opens in new tab)
Financial Conduct Authority Regulatory Consultation, 2025
Contributed expert analysis to the FCA's consultation on stablecoin regulation and the future of crypto asset oversight in the UK. Provided evidence-based commentary on regulatory frameworks, consumer protection mechanisms, and systemic risk considerations for digital assets.
UK Government Business Academy - AI Webinar Series
Department for Business and Trade, Business Academy, 2025
Delivered a series of three official UK Government Business Academy webinars on AI adoption for growing businesses, led by Dr Stylianos Kampakis. Topics covered: designing AI roadmaps, choosing the right AI tools using the OCT (Objectives-Capabilities-Tools) methodology, and building internal AI capability including skills-gap analysis and organisational models for long-term success.
Open Governance: Open-Source AI Governance Server (opens in new tab)
Open-Source Tool, Ongoing
An open-source AI governance platform that helps organisations discover, assess, and monitor AI systems against EU AI Act, NIST AI RMF, and ISO 42001 frameworks. Provides automated risk classification, compliance matrices, bias and hallucination monitoring, policy enforcement gates, and audit-ready reporting through 48 governance tools.
London Data Week 2026: AI Tools for Everyone, Advancing Disability Inclusion (opens in new tab)
London Data Week, LSE, 8 July 2026
Returning bigger in 2026 at the London School of Economics. Tesseract Academy is hosting a public session bringing together speakers from technology, disability, research and policy to explore how AI can advance accessibility and support for people with diverse disabilities. Wednesday 8 July 2026, 4 to 6pm, Shaw Lecture Theatre, LSE. Free, registration via Eventbrite.
London Data Week 2025: AI Tools for the Visually Impaired (opens in new tab)
London Data Week, co-organised with Vision Ability CIC, 2025
Co-organised a public workshop and demonstration on making AI tools accessible to people with visual impairments. Delivered at Chabad Islington Community Centre as part of London Data Week 2025, in partnership with Vision Ability CIC.
