Fabraix GTM brain
Fabraix sells Nyx, an automated security testing agent for organizations deploying customer-facing AI agents.
category
AI agent security testingmarket profile
- text: Customer-facing agents change with their models, permissions and tools, creating a need for repeated security testing.
- text: AI security buyers can choose automated red-team platforms, open-source test frameworks or traditional security engagements.
personas
- title: Head of application securitypains:
- A one-off red team becomes stale as agent behavior and integrations change.
- Needs reproducible findings that engineering teams can validate and fix.
- title: AI product engineering leaderpains:
- Customer-facing agents can fail in ways ordinary application testing does not reveal.
- Release cycles outpace manually scheduled adversarial testing.
- title: CISO at a large enterprisepains:
- Needs evidence to support release decisions for AI handling customer interactions.
- Must manage testing expense across a growing estate of agents.
icp
- text: Enterprises shipping customer-facing AI agents, including large companies with security review requirements.
- text: AI product teams whose agents change frequently and interact with external systems or content; no fixed headcount threshold is published.
message pillars
- text: Continuously test customer-facing AI for security weaknesses.
- text: Connect findings to engineering remediation.
- text: Build trust through adversarial testing.
objections
- objection: Will this expose internal systems or require source access?response: The vendor describes Nyx as black-box; confirm target access, permitted scope and data handling for the planned test.
- objection: How is it better than our existing open-source red team framework?response: Run both on an authorized representative agent and compare useful validated findings, coverage and engineering effort.
competitors
- name: Promptfoowhy: Offers developer-oriented AI evaluations and red teaming.
- name: Mindgardwhy: Commercial platform for testing and red teaming AI systems.
- name: Giskardwhy: Offers AI testing and continuous agent red teaming.
keywords
- AI agent red teaming
- automated AI security testing
- AI agent vulnerability assessment
- LLM security testing
- agent security evaluation
- continuous AI red teaming
voice
- Technical and adversarial
- Confident and direct
- Security practitioner focused
signals
- text: A company launches a customer-facing agent or grants it new integrations and permissions.
- text: An application security team is establishing repeatable AI security testing before releases.
hiring
- AI researchers
- Product engineers
- Forward-deployed engineers
pricing
model: unknown
motion
sales_ledchannels
- YC launch
- public playground
confidence
mediumFounders
- name: Ahmed Alytitle: Founder/CEOrole: CEObio: Co-founder @ Fabraix, building a frontier hacker agent that finds failure modes and security exploits in AI systems before real users do. Previously the first data scientist at Sequoia-backed Two, where he built AI systems for adversarial environments from scratch and scaled them to process $1B+ in annual B2B transactions, averting $50M in losses for multiple Fortune 150 companies. A published researcher with multiple papers in Q1 journals and a UCL PhD drop-out.
- name: Ibrahim Abdutitle: Founder/CTOrole: CTObio: Red-teamed AI agents in Meta's Privacy org; built an SRE agent triaging 3M+ errors/month, saving 10,000+ engineering hours a year. Built a compiler for insider-trading detection at TradingHub: $100M+ in daily trades; Oxford PPE, top 8% of cohort.