Identify Public Infrastructure and Security Decision-Makers at Frontier AI Labs

Outcome

Help me identify the email addresses and phone numbers for the Create a structured research report identifying public, business contact information for decision-makers at the following AI labs who would be responsible for confidential inference, private model hosting, secure compute infrastructure, or AI platform engineering.

Target companies: Thinking Machines Lab, SSI (Safe Superintelligence), Skild AI, Poolside, Reflection AI, Project Prometheus, Physical Intelligence, Unconventional AI, Humans&, Inflection AI, Isomorphic Labs, AMI Labs, Decart, Xaira Therapeutics, Sakana AI, General Intuition, Liquid AI, H (The H Company), Magic, Periodic Labs, Harmonic, AI21 Labs, Lila Sciences, Chai Discovery, Flapping Airplanes, Recursive, World Labs, EvolutionaryScale, AAI, Kyutai, Goodfire, Imbue, Reka, Essential AI, Zyphra, Nous Research, Aaru, Simile, Isara, Moonvalley, Hark, Prime Intellect, Ndea, Inception Labs, Adapting Labs, Elarion, Genesis AI, CuspAI, Poetiq, Axiom Math.

Prioritize the following roles, or closest equivalents. Tier 1: Chief Technology Officer, Chief Scientific Officer for biotech AI companies, VP Engineering, VP Infrastructure, Head of AI Platform, Technical Co-Founder. Tier 2: Head of ML Infrastructure, Director of Platform Engineering, Head of AI Infrastructure, Principal Infrastructure Engineer, Head of Agents. Tier 3: Chief Information Security Officer, Director of Security Engineering, Head of Privacy Engineering.

For each company, identify the most relevant individual in one of the roles above and provide results in a structured table with the following columns: Company, Name, Title, LinkedIn URL, Work Email (publicly listed only), General Company Contact Email, Public Business Phone Number, Confidence Score from 1 to 5, and Sources.

Only use publicly available information from company websites, press releases, LinkedIn public profiles, Crunchbase, conference bios, or other open sources. Do not use private emails, personal phone numbers, scraped databases, leaked data, or paywalled sources. If a direct work email is not publicly listed, you may include a likely company email pattern such as firstname@company.com , but clearly label it as unverified and reflect that in the confidence score. Each contact must be supported by at least two independent public sources, and titles should be verified as current within the last six months when possible.

The objective is to produce a compliant, high confidence outbound contact list of infrastructure and security decision-makers at AI-native companies that may require confidential inference or private model hosting.

Data Analysis Request

Data Source

Use any available sources including company websites, press releases, LinkedIn public profiles, Crunchbase, conference speaker bios, GitHub profiles if contact information is publicly listed, and other open web sources.

Questions to Answer

Who is the most relevant decision-maker at each target company responsible for confidential inference, private model hosting, secure compute infrastructure, or AI platform engineering?

What is their current title and does it match one of the priority roles: CTO, Chief Scientific Officer (biotech), VP Engineering, VP Infrastructure, Head of AI Platform, Technical Co-Founder, Head of ML Infrastructure, Director of Platform Engineering, Head of AI Infrastructure, Principal Infrastructure Engineer, Head of Agents, CISO, Director of Security Engineering, or Head of Privacy Engineering?

What publicly listed business contact information is available for this individual, including work email if published, general company contact email, and public business phone number?

What are at least two independent public sources that verify their title and company affiliation?

What is the confidence score from 1 to 5 based on recency, source quality, and contact verification?

Deliverable Format: csv