AI R&D for defence — validated against adversaries, not edge cases.
Radar AI, digital twins, multi-sensor fusion, operational simulations, cognitive defence. EU-sovereign IP, no ITAR. Battlefield-validated methodology, calibrated against operational data from Ukraine — adversarial conditions no European synthetic dataset covers.
Five Competency Areas
Five capabilities. One foundation:
AI systems that are certifiable, explainable, and validated against real adversarial data.
01
AI Governance
Certification-ready architecture
EU AI Act and NATO AI Strategy require technical evidence of governance — model cards, traceability, audits. We embed model traceability, decision logging, human-oversight gates, and audit pipelines from day one. Defence-grade AI that passes EU AI Act high-risk audits without redesign. Aligned with EU AI Act, NIST AI RMF, NATO Responsible AI.
02
AI Risk Assessment
Where defence AI actually fails
Defence AI breaks in three ways primes rarely test for: adversarial inputs, distribution shift (lab data ≠ battlefield), and emergent failure modes in fused multi-sensor systems. End-to-end framework: threat modelling for ML systems, adversarial robustness testing, distribution-shift monitoring, red-team evaluation pipelines. Delivered as audit (existing systems) or integrated layer (new R&D).
03
Radar AI / Digital Twins
Sim-to-real for sensor ML — LEAD CAPABILITY
The bottleneck in defence AI is not models — it is data. Real RF environments — contested or jammed — cannot be reproduced at scale. Primes spend 18–36 months collecting field data before models are deployable. New threats (drone swarms, frequency-hopping UAVs, spoofing) outrun this cycle.
Deliverables
- RF environment simulator (passive + active radar regimes)
- Synthetic data pipeline for ML training at scale
- Sim-to-real validation against real captures
- Multi-sensor fusion (RF + acoustic + optical)
04
AI Simulations
Multi-agent operational ConOps
C2 systems, sensor networks, and counter-UAS architectures are designed against assumptions, not evidence. Real-world performance under saturation, multi-vector attack, or degraded comms is unknown until deployment. We deliver multi-agent operational simulation: drone swarms, sensor degradation, jamming, operator decision load. Modular stack compatible with existing prime platforms.
05
Cognitive Defence
Detect · Analyse · Train
NATO ACT recognises cognition as an operational domain. Three integrated capabilities:
- FIMI Pulse — OSINT monitoring with auto-tagging in DISARM taxonomy (EEAS standard). Real-time threat briefs. STIX 2.1 export.
- DISARM Workbench — analyst tool for manual + AI-assisted tagging of information incidents. Campaign linking, actor graphs, CTI-ecosystem integration.
- Inoculation Platform — scenario-based training built on peer-reviewed inoculation theory. Ukrainian wartime corpus as content moat. Multi-language.
Built on NATO ACT framework + EEAS DISARM/FIMI taxonomy + Cambridge/Lund inoculation theory.
Battlefield-Validated Data — The Moat
The differentiator
no European competitor can offer.
Operational RF, EW, and drone-threat data from Ukrainian critical infrastructure operations. Adversarial conditions captured live — drone signatures, frequency-hopping UAVs, EW jamming patterns, spoofing attempts, fused multi-sensor failure modes — under conditions no synthetic dataset and no peacetime test range reproduces.
500+ documented operational crisis logs from Ukrainian critical infrastructure operators. Legal and ethical framework for EU-compliant R&D use. Calibrated, governed, available to consortium partners under appropriate agreements.
This is the dataset European synthetic environments cannot generate and US partners cannot transfer without ITAR friction.
Snapshot
18–36 mo
Typical field-data cycle (industry baseline)
>90%
Sim-to-real transfer retention
97%+
Multi-sensor fusion classification confidence
500+
Operational crisis logs (Ukrainian critical infrastructure)
Why Talan.tech for Defence
Three things
European competitors cannot offer.
01
Battlefield-validated data
Operational RF, EW, and drone-threat data from Ukraine. Legal and ethical framework for EU-compliant R&D use. Not available to any other European partner.
02
EU-sovereign IP, no ITAR
Clean for EU defence procurement, Horizon Europe, EDF, EUDIS. No US re-export risk. No clearance bottlenecks.
03
Full-stack accountability
Same team designs, trains, validates, governs, certifies. One accountable counterparty for the full AI lifecycle. No hand-off gaps.
Engagement Models
How we work with primes and programmes.
R&D Subcontracting
Talan.tech as AI/ML R&D supplier within prime-led programmes. MOLINA-style consortium model. EDF / Horizon Europe / EUDIS calls.
Joint Consortium
Co-bid on upcoming EU/NATO calls. Prime leads system integration, Talan.tech leads AI/ML workstreams. Specific calls per quarter.
Framework Agreement (MSA)
Talan.tech as preferred AI R&D vendor across multiple prime programmes. Pre-negotiated terms, faster activation per project.
Procurement Readiness
Built for European defence procurement.
EU-incorporated entity
Clean legal counterparty for EU programmes
No ITAR / no US re-export risk
No clearance bottlenecks for joint EU work
Horizon Europe / EDF / EUDIS-eligible
Registered, ready, prior consortium experience
NATO Responsible AI aligned
Methodology cross-walked against NATO AI Strategy
Next Step
30-minute working call.
Map your programme pipeline.
We map your programme pipeline against the five competency areas. Capability deck available on request.