Verification & Trust.

Thesis

Why this sector, why now.

As agents transact and models earn on their own, the unanswered question is verification: did the inference actually run, on the model claimed, producing the output that got paid for? zkML, optimistic ML, and proof-of-inference turn "trust me" into "verify me." This is the bucket where Lookout's CertiK relationship is a genuine edge — auditing and proof systems are adjacent disciplines, and no neutral platform covers verifiable AI with audit-grade credibility. The fork: do proofs live at the model layer (zkML — EZKL, Modulus, Giza) or the coprocessor layer around it (Lagrange, Space and Time)? My read: zkML is still too expensive for large models, so near-term value accrues to optimistic and coprocessor approaches; zkML wins later as proving costs fall.