Company · About & team
We build the evidence layer AI approval was missing.
AetherLab is an AI risk company in San Diego. We red-team AI systems, contain their failures in production, and turn the results into evidence that risk teams, underwriters, and procurement committees can act on.
Started in adversarial research. Forged in production.
AetherLab's founding research question predates the current AI wave: how do you know when a machine-learning system will hold up against inputs designed to break it? Our founder's doctoral work on the adversarial robustness of classifiers was peer-reviewed at IEEE ICMLA in 2019, before adversarial AI was a commercial category.
The commercial insight came later, from the other side of the table. Working on applied AI at BCG GAMMA and risk systems at Gemini made one thing obvious: the hard part of enterprise AI was never the demo. It was the approval: the moment a risk team, a bank, or a regulator has to decide whether the system is safe enough to stand behind, with no standard evidence to decide on.
So that's what we build. AdversarialScan finds how a system breaks. Guardrails hold the line in production. The Evidence Pack turns both into a record an institution can approve. Today that infrastructure screens 150,000+ AI checks a day, text and image, for platforms and institutions with real content risk.
What we believe
- Evidence over assurances. Every claim we make about a system is reproducible; every number we publish is measured.
- Severity over pass/fail. Real risk decisions need ranked findings tied to consequences, not a green checkmark.
- Depth over theater. We publish our research where we can, keep our attack methodology private on purpose, and skip the logo walls.
Built by
- Published adversarial-ML research (IEEE, 2019)
- PhDs in physics, statistics, and computer science
- Alumni of BCG, McKinsey, and Gemini
- Production AI risk systems in payments and fintech
- Advised by a former CISO of Twitter, CrowdStrike, and F5 and a former Lloyd's Syndicate 1200 active underwriter
Researchers who ship, operators who measure.
Physics PhD (UC San Diego, 2019) whose published research covered the adversarial robustness of machine-learning classifiers, peer-reviewed at IEEE ICMLA in 2019 before adversarial AI was a commercial category. Worked on applied AI at BCG GAMMA and on AI-driven risk systems at Gemini before founding AetherLab.
- ·Published adversarial-ML research (IEEE ICMLA 2019)
- ·PhD in physics, UC San Diego
- ·BCG GAMMA · Gemini
PhD in statistics from UC Santa Barbara with published machine-learning research under the name Jinwen Qiu, including the LIFE interpretability framework, plus a machine-learning patent and fraud-detection ML at Gemini. Owns the engineering discipline that keeps AetherLab serving production traffic every hour.
- ·PhD in statistics, UC Santa Barbara
- ·Published ML research (JMLR 2018; Neural Computing & Applications, 2023)
- ·Production ML & fraud systems at Gemini
Machine-learning researcher: co-author of Decoding Biases, red-teaming and bias-detection research presented at a NeurIPS 2024 workshop, and former Senior AI Research Scientist at Intel Labs. PhD in computer science from CU Boulder and former assistant professor at the University of Kansas, where her research drew NSF, DARPA, and NASA funding.
- ·Co-author, Decoding Biases (NeurIPS 2024 workshop)
- ·Former Senior AI Research Scientist, Intel Labs
- ·PhD in computer science, CU Boulder
Operator and strategist: COO of a Y Combinator-backed startup and an alum of McKinsey and BCG, with experience leading large-scale digital transformation programs. Keeps AetherLab pointed at the problems institutions actually pay to solve.
- ·COO of a YC-backed startup
- ·McKinsey & BCG
- ·Large-scale transformation programs
Twenty years building commercial engines for B2B technology companies, most recently six years building Dolphitech's commercial function across a 20-country partner network. Co-founder of S.L.A.M. Commercial Partners, which runs commercial due diligence for PE and VC investors; owns AetherLab's payments go-to-market.
- ·~20 years in B2B technology sales
- ·Co-founder, S.L.A.M. Commercial Partners
- ·Owns payments go-to-market
More than twenty years in B2B sales across Europe, the US, India, and China, including over a decade leading CPG sales for Central Europe at Mintel, and author of Sales Is Not Rocket Science, But a Simple Art. Co-founder of S.L.A.M. Commercial Partners; owns AetherLab's enterprise go-to-market.
- ·20+ years of B2B sales across Europe, the US, and Asia
- ·Co-founder, S.L.A.M. Commercial Partners
- ·Owns enterprise go-to-market
Product and UX leader: UX leadership roles at Comcast and Capital One, product at C2FO, a working-capital fintech where reliability is a requirement rather than a feature, and founder of Munchkin Mailbox. Responsible for making rigorous risk tooling feel usable.
- ·UX leadership at Comcast & Capital One
- ·Product at C2FO (fintech)
- ·Founded Munchkin Mailbox
Advisors
Operators who have run the functions our customers answer to: security leadership and specialty-insurance underwriting.
Security chief with three decades leading security organizations: CISO at Twitter, CrowdStrike, and F5, Chief Security Officer at Resilience, and creator of CrowdStrike's Falcon OverWatch managed detection and response service. A retired US Air Force Colonel with a patent on detecting malicious network activity, he advises AetherLab on technology and product.
- ·CISO at Twitter, CrowdStrike & F5 · CSO at Resilience
- ·Created CrowdStrike Falcon OverWatch
- ·Retired USAF Colonel · network-security patent
Global insurance executive with 30+ years of underwriting leadership across the commercial and specialty insurance and reinsurance markets: active underwriter of Lloyd's Syndicate 1200 at Argo, Global Chief Underwriting Officer at Innovisk Capital Partners, and senior underwriting roles at Hiscox and elseco. A trained mechanical engineer who began his career on Ariane launch operations at the French space agency CNES, he advises AetherLab on insurance and underwriting.
- ·Active underwriter, Lloyd's Syndicate 1200 (Argo)
- ·Global CUO, Innovisk Capital Partners
- ·30+ years in specialty insurance & reinsurance · HEC Paris MBA
The team keeps growing across engineering, research, and go-to-market. Interested in joining our team? Reach out to us at hello@aetherlab.co. We're hiring →
The work is on the record.
Our published research is in adversarial robustness and model evaluation: the defensive science. The attack methodology inside AdversarialScan is proprietary and deliberately unpublished; the credentials behind it are not.
A. Georges et al. · IEEE ICMLA 2019 · DOI ↗
Peer-reviewed work on robust classification: adversarial-ML research published before adversarial AI was a commercial category.
A. Georges · BCG GAMMA (Medium)
An accessible account of the shape-of-data methods behind robust classification, including what adversarial examples reveal about model fragility.
A. Georges · UC San Diego, 2019
The research foundation: mathematical structure as a lens on model behavior and robustness.
S. Kumar, N. Beckage, et al. · NeurIPS 2024 workshop (Red Teaming GenAI)
Team research on adversarial prompting and automated methods for evaluating bias in language models.
J. Qiu et al. · Neural Computing & Applications, 2023
Team research on measuring the internal representations neural networks actually learn.
Work with the team.
Approving AI, building it, or writing about the space: we respond within one business day.
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