Helping CTOs build AI systems that won't fail in production.

Most AI systems fail in production not because the models are wrong, but because the architecture wasn't built for the real world.

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Daniel Jacobsen

This is for you if

  • Your AI works in the lab but breaks down under real usage
  • You've shipped a prototype but can't get it to hold up in production
  • You need senior AI systems expertise, not more ML research
  • You want architecture designed around risk, traceability, and real-world constraints

This is not for you if

  • You're looking for a data science contractor or ML researcher
  • You want off-the-shelf tooling, not custom architecture
  • Your challenges are not mission critical