My AI-driven automation project is finished in terms of features, but it refuses to run. Somewhere between launch and final output the execution breaks, yet I can’t isolate whether the problem lies in initialization, data handling, or result generation. I need fresh eyes to trace the fault, correct it, and hand the code back in working order. You’ll be reviewing an existing codebase that mixes Python, a small JavaScript front end, and one Java microservice. I can grant repository access, sample data, plus a short rundown of the intended workflow. From there, I’m looking for: • Pinpointed diagnosis of the failure • All necessary code fixes or configuration tweaks • A concise changelog so I understand what was altered The job is complete once the automation runs end-to-end on my machine without errors and produces the expected output. If you’re comfortable debugging multi-language AI pipelines, I’d love your help getting this over the finish line.