Guardrails that let teams adopt AI and run sensitive work without exposing data, identities or intellectual property.
AI adoption tends to run ahead of governance. Data leaves controlled boundaries, agents gain more autonomy than intended, and sensitive activities such as investigations, M&A research and OSINT happen on production laptops.
CyberLane helps leadership set the boundaries: what data may be used, which decisions require human oversight, and where isolated environments should replace ad-hoc practice.
Policy, ownership and approval paths for AI use, sized to the organisation rather than borrowed from a framework.
Defining which data classes may reach which models and services, and how that is enforced and evidenced.
Reviewing autonomy levels, tool access, prompt and output handling, and failure modes for agentic workflows.
Deciding where a person must remain in the loop, and designing review points that are practical to sustain.
Guidance on isolated environments for investigations, M&A, OSINT and AI experimentation away from production.
Assessing how vendors and partners apply AI to your data, and what to require contractually.
Advice comes first: the requirements decide the technology, not the other way round. Where a product is warranted in this domain, these are the ecosystem technologies we most often assess.
Considered where AI experimentation, research or sensitive work should run in isolated, disposable environments away from production.
Vendor overview and FAQsConsidered where AI and data platforms need a hardened, low-CVE base layer with verifiable provenance.
Vendor overview and FAQsCyberLane advises on governance, architecture and requirements. Environment build-out and product configuration are coordinated with the relevant technology vendor or a qualified implementation partner.
A short consultation is usually enough to frame the problem, agree the scope and outline a practical next step.