AI-verifiable interview room

Test the evidence and stress the design

A production ML interview room that keeps documented work, supported extrapolation, proposed approaches, and unknowns visibly separate.

Bring a role or a system problem

Map a role to cited evidence or generate a non-binding design review under explicit scale, privacy, latency, cost, and model-policy constraints.

Explore six engineering guides

Choose document intelligence, production reliability, agent engineering, private AI, forecasting and data engineering, or data correctness and cloud migration from Explore with AI or the header Guides control. Each path opens relevant case studies, highlights an architecture decision, and leads to a demonstration you explicitly run before creating a cited takeaway.

Takeaways distinguish recorded evidence from live sample extraction, simulated failures, browser tool-contract validation, on-device semantic or keyword search, browser forecast baselines, and source-to-target table reconciliation. These demonstrations do not reproduce private production systems.

Challenge every claim

Claim receipts expose assertion type, source boundary, counterarguments, missing evidence, revision conditions, and interview questions.

Privacy controls

Problem text is processed transiently. Restricted client and internal project names remain excluded from the public registry.

Private search on your device

Search six public case studies using MiniLM embeddings computed in your browser. Model loading is explicit; queries and embeddings stay in tab memory. Inspect source passages, similarity scores, and measured latency, or use the download-free keyword search.

Open the browser-local search lab.

Review the full delivery record or read the AI trust centre.