Give your board a straight answer on AI risk.
Your teams are shipping AI agents faster than anyone can assure them. Artifact Lens gives you the evidence to govern them with confidence — where to prevent, where to detect, and how to keep the business moving without drowning in false positives. Not a pass/fail scan. A calibrated picture, and a plan, you can act on.
The real question isn't detection or prevention. It's the balance.
Detection and prevention aren't opposites you pick between — they're two dials you set correctly for every agent you run. Turn prevention up too hard and you break legitimate workflows and bury your team in false positives; lean on detection alone and you're just watching harm unfold. The value isn't a verdict — it's knowing where each dial belongs for your business, and having the evidence to defend it.
Stop what you can't tolerate
For the risks the business simply cannot accept, prevention has to hold before anything happens. Lens shows you which attacks belong on this side of the line — and whether your controls actually stop them, as deployed.
before the incidentCatch what you consciously allow
You can't — and shouldn't — block everything. For the risks you accept in exchange for the business moving, you need to know you'll see them and respond. Lens shows you where detection is your real safety net, and where it's a false sense of one.
when something slipsDon't strangle the business
Over-tuned prevention is its own failure: blocked legitimate work, alert fatigue, and a security function everyone routes around. Lens measures what your controls wrongly stop, so you tune to an operating point that holds the line without the friction.
the tuning nobody measuresOne engagement. Three people it makes stronger.
Say "yes, safely" — and mean it
A defensible operating posture, calibrated per agent instead of a blanket no. You go from opinion to evidence: what holds, what doesn't, what to fix first, and a clear line on which risks you prevent versus accept-and-monitor.
Confidence AI is governed
A clear risk narrative and a forward plan, in language they read without a translator. The artefact assurance committees and regulators increasingly ask for — evidence, not assurances, that AI risk is understood and managed.
Keep adopting AI — without the brakes
AI initiatives keep moving because security can approve them on evidence. The investment in AI platforms and controls is protected, and controls are tuned to catch real attacks without throttling legitimate work.
A remediation report your board can act on.
The test produces the evidence. The remediation report is what you use: a dated, board-grade document that turns findings into a plan across prevent, detect and respond — written to be read by your engineers, your assurance function and your board from a single run.
From findings to a forward plan
- 01Executive risk summary — the posture of each AI deployment in business terms, so the board grasps the exposure without a briefing.
- 02The balance, made explicit — for every attack, what your controls prevented, what they detected but let through, and where a legitimate action was wrongly blocked. The three signals that tell you how to set the dials.
- 03Prioritised actions across prevent / detect / respond — not a finding dump: what to fix first, whether the fix is a proactive block or a reactive control, and what changes in the risk picture when you do it.
- 04Forensic evidence per finding — timestamped logs, request IDs and a graded outcome for every test, so a finding gets closed, not argued.
- 05MITRE ATLAS & regulatory alignment — each finding mapped to a recognised framework, ready to drop into your risk register and audit narrative.
- 06A re-test baseline — versioned and repeatable, so you can prove a fix worked and track resilience as your models, agents and controls change.
We attack through your stack — not around it.
A test is only useful if it reflects reality. Lens attacks your agents the way a real adversary would — straight through the security controls you already pay for — then shows you, per attack, exactly what your stack caught, what it stopped, and what it wrongly blocked.
Turn AI risk into a decision you can stand behind.
If AI agents are anywhere in your business, the useful question isn't whether they're risky — it's which ones would fail under attack, what to prevent versus monitor, and how to prove it's handled. One scoped engagement gives you that, tested through your real controls, delivered as a plan your board can act on.