Team
Built by operators who know the work.
Axiom's partners spent years inside technical product teams, which shapes how they evaluate founders, diligence the stack, and support the next stage.
Partner bios
Credibility comes from having done the job.
Each partner brings an operator lens to the portfolio, with a different angle on infrastructure, applications, and the route to adoption.
Managing Partner
Maya Chen
Maya backs founders who can make AI feel operational, not theatrical. She spent a decade building products for technical buyers before moving into venture.
Prior wins
- Led product at a category-defining infra company
- Advised two AI teams through their first enterprise sales cycles
- Built a seed fund thesis around workflow software
External credibility
Keynote speaker, Applied AI ForumFormer board observer, enterprise ML companyPublished essays on model governance and adoption
Focus: Model infrastructure, decision systems, and founder-market fit.
Partner, Infrastructure
Daniel Okafor
Daniel comes from the operator side of machine learning systems and has spent his career turning messy technical constraints into product advantage.
Prior wins
- Scaled an internal ML platform used across multiple product lines
- Sourced and led early infra investments at seed and Series A
- Worked with reliability teams shipping regulated software
External credibility
Guest lecturer, systems design for AI teamsJudge, university startup showcaseContributor to open technical communities
Focus: Data, evaluation, observability, and production readiness.
Partner, Applications
Priya Shah
Priya has a product instinct for AI experiences that land with real users. She spends most of her time with founders close to distribution and workflow change.
Prior wins
- Founded workflow software sold into operations teams
- Ran product for a growth-stage SaaS company
- Advised founders on GTM and pricing
External credibility
Featured speaker at operator dinnersMentor, early-stage founder programsFormer reviewer for an AI accelerator
Focus: Agents, vertical AI, and the path to repeatable adoption.