Five kinds of teams, sorted by AI engineering maturity, not industry.

Technical leaders now control 72% of enterprise AI purchasing power. We organize around that: how mature a team's AI engineering already is and what's actually blocking production, not which industry vertical they sit in.

How we qualify fit.

Instead of qualifying by industry, we qualify by engineering signals.

SignalGood fitPoor fit
CloudAWS / Azure / GCPOn-prem only
ContainersKubernetesNone
Source controlGitHub / GitLabLegacy SCM
InfrastructureTerraform / PulumiManual
AI usageLLMs, agents, RAGNo AI initiatives
Engineering size10+ engineersFewer than 5 engineers
Platform teamYesNo
APIsMature API ecosystemMonolith only

Who's actually in the room.

Technical leadership has become the center of AI purchasing decisions, with engineering evaluation typically preceding commercial approval.

ChampionTechnical BuyerEconomic BuyerApprovers

Champion

  • Platform Engineer
  • AI Engineer
  • ML Engineer

Technical Buyer

  • Head of Platform Engineering
  • VP Engineering
  • Head of AI

Economic Buyer

  • CTO
  • Chief AI Officer
  • CIO

Approvers

  • Security
  • Enterprise Architecture
  • Procurement
  • Legal

Common questions.

Not sure which profile fits? We'll tell you in 30 minutes.

Bring us where your team actually stands, engineering size, AI maturity, what's blocking production, and we'll tell you honestly whether we're a fit before we recommend anything.

Talk to an AI Engineer(opens Calendly in new tab)30 minutes · No slide deck · No sales pitch

No hype · No forced roadmap · Just a clear view of whether we're the right fit