ReKit — Visual Recovery Intelligence

Incomplete returns can contain complementary parts, but a plausible visual match is not enough to rebuild a compatible kit. ReKit connects uncertain visual evidence to accountable recovery decisions. The prototype preserves original images and hashes under unique physical-component identities. Local Qwen3-VL-2B-Instruct inference on NVIDIA hardware records observations, uncertainty and source references. Humans verify or correct those claims; approved BOM and revision rules determine compatibility. CPU OR-Tools CP-SAT compares rebuilds, liquidation, donor retention and holds. Atomic reservations reject conflicting allocations, and explicit completion records preserve kit lineage. Two separate demonstrations show this boundary. Original Amazon Berkeley Objects catalog photographs support actual local visual inspection in simulated intake; they are not customer-return photographs. A scripted synthetic case uses three returns and four components: revision B is rejected, a new close-up requires review, and a recorded A correction enables two synthetic kit completions. Under baseline assumptions the modeled rebuild value is $175, compared with $102.50 whole-return liquidation and $16 noncash retention. Raising labor costs changes the preferred decision to $85 liquidation. These are scenario estimates, not sales or measured savings. ReKit is a validated local prototype, not a production deployment. Human semantic accuracy has not been measured. Actual AMD-hosted inference and application integration remain pending after two HTTP 400 attempts; NVIDIA execution does not satisfy AMD qualification. The contribution is the auditable connection between evidence, human authority, constrained allocation and controlled execution.