Four practices, one standard of rigour
From advisory work in the boardroom to models in production, every B86N engagement is explainable, auditable, and designed for the institutions that operate under scrutiny.
AI Consulting
AI Model Building
AI Training
Media Intelligence Platform
Built for the scrutiny your work invites
Most AI vendors optimise for demos. We optimise for the audit. Every system we deliver is designed to be explained, defended, and operated in environments where the consequences of a wrong answer are real.
EU AI Act standards
Compliance isn't bolted on — it's the brief. Documentation, risk classification, and conformity considerations sit at the centre of every engagement.
Fully explainable
Every output is auditable. Why the model decided what it did — and what evidence supports the decision — is exportable in a form your auditors and your courts can read.
Human-in-the-loop
Critical decisions are reviewed by people, not approved by silence. We design workflows where AI scales judgment — it doesn't replace it.
Proprietary algorithms
No black-box dependencies on third parties whose roadmap and policies you don't control. Models built and owned alongside you, deployable in your environment.
Multi-model ensemble
For detection and verification, we combine multiple specialised models rather than betting on one. Higher accuracy, narrower failure modes, defensible in adversarial settings.
Unified platform
One workspace for text, image, video, and audio — across the full breadth of public and non-public sources your investigation requires. No tool sprawl, no analyst context-switching.
Principles that don't bend for the engagement
Whether we're advising your board, building a model for your data, training your analysts, or operating the platform for your institution — the same standards apply. They're what make our work hold up after the demo is over.
Verify first
Authenticate every name, date, and statistic before it leaves the system. Confidence is earned per claim — not assumed at the source.
Independent validation
Confirm findings against an authoritative source, or against multiple independent data points. One source is a lead — not a conclusion.
Cross-source triangulation
Cross-reference findings across multiple independent sources and channels. The picture only becomes complete when sources that don't talk to each other agree.
Fact vs. opinion
Maintain a strict separation between evidence-based findings and subjective interpretation. Output that conflates the two is output we don't ship.
Talk to us about your engagement
Whether it's an advisory conversation, a model build, a training programme, or a platform demo — we come back with a structured response.
Request a demo