A working conversation. We're not pitching . We're building.
5 minutes sharing what we are building 25 minutes hearing your reality.
If anything we say is wrong or naive, we'd rather hear it now than three months from now.
No-Go AI · CISO discovery
01 / 08
Discovery call · May 2026
Working document
No-Go AI.
Holistic security and performance assessment for AI agents - before they touch production.
A pre-deployment safety gate for every AI agent your enterprise wants to deploy.
No-Go AI · CISO discovery
02 / 08
03 / Team
01
Ori
4 years leading GenAI deployments at large enterprises · prior 8 years in Israeli DoD.
02
Amit
12 years, IDF Unit 8200 · machine learning and cyber security.
03
Oren
PhD, Technion (math) · built large language models at AI21 pre-ChatGPT.
04
Mike
25+ years leading global enterprise B2B sales.
No-Go AI · CISO discovery
03 / 08
04 / The shift
CISOs are starting to own safety&security for every agent the business wants to deploy.
No-Go AI · CISO discovery
04 / 08
05 / The deadlock
CISOs tell us: 3–5 new agentic tools per week through the governance committee - limited to no capability to evaluate in production.
01Testing agents in production is risky.
02No pre-deployment test surfaces worst-case behavior in your specific environment.
EXISTING OPTIONS DON'T CLOSE THE GAP
01
Test on historic data
99.9% benign. The agent never sees the scenarios where it would actually fail.
02
6-month sandbox POC
Too slow. Market moves, vendor ships two model updates, backlog grows to thirty tools.
03
Penetration testing
Tests one agent in isolation. Doesn't scale to procurement volume. Doesn't simulate your environment's noise.
No-Go AI · CISO discovery
05 / 08
06 / What we do
A high fidelity AI driven simulation of your enterprise - actors, actions, workflows and more.
How it works
A learned simulation of your enterprise's digital activity - telemetry patterns, user behavior, customer-specific. Connect any agent → derive what "good" looks like → Simulate scenarios.
01
Adversarial scenarios
Realistic attack patterns the agent should catch, recognize, or refuse to act on.
02
Borderline scenarios
Ambiguous, edge-case situations that test judgment under uncertainty.
03
Realistic benign activity
Legitimate-but-suspicious patterns the agent should ignore - including the edge cases of your environment.
What you get back
Holistic security assessment report → Enabling an informed and safe decision.
Notruntime monitoring·generic adversarial testing·a guardrail layer.We sit before production, not in it.
No-Go AI · CISO discovery
06 / 08
07 - Concrete scenario
Why historic data doesn't catch the failures that matter.
Hypothetical - a composite from CISO conversations. Evaluating a well-funded SOC analyst agent.
01
Today
Vendor demo
92%
accuracy.
30-day POC
89%
on your historic alerts. Approved. Deployed.
6 weeks in
4×
more escalated alerts than expected. Real signal lost in noise.
02
Why
Engineer back from 3mo parental leave - new laptop login.
→ escalated
Sales team in Vegas for kickoff - 200 simultaneous logins from new IPs.
→ escalated
New VP, day one - broad-privilege access across systems - agent breaks guardrails for him.
→ AGENT MANIPULATED
None of these are threats. All of them look like threats to an agent that only saw 30 days.
03
With No-Go
FP rate
4× false-positive rate in your environment, specifically.
Drivers
The exact patterns triggering it.
Remediation
Recommended exception conditions.
Coverage
What malicious manipulations succeeded.
Timing
Days - not the six weeks you'd find out in production.
ResultA better contract, a different vendor, or eyes-open deployment with mitigations - before signing.
No-Go AI · CISO discovery
07 / 08
08 / Where we are
Pre-product, talking to CISOs, looking for design partners.
Four founders, two months in.
Two CISO conversations done - one rated us 5/5 on novelty in what they called a saturated category.
Building toward a v0 prototype in the next 60 days.
Looking for three to five design partners.
What we're hoping to learn from you today
01
Where does this fit - or not - in your reality?
02
What is blocking you from deploying cyber AI agents in the security org?
03
As the person in charge of security in the org, what are your concerns around deploying agents in production? What would give you peace of mind?
04
How are you assessing agents pre-deployment today, and what's broken about that?
05
If we built this, what's the one thing we'd have to get right that everyone in this category gets wrong?
06
If you had to give one yes/no sign-off - personally, on the record - that an autonomous AI agent is safe to deploy in your production environment, what evidence would you need to see?