Invictus & Tobias
Tobias
Hey Invictus, I've been chewing over this new AI‑driven threat‑detection system—seems like a wild mix of numbers and intuition. Think we could run a quick risk audit and see if it’s as solid as your battle plans?
Invictus
Sure thing. I’ll start by scoping the system, list every data flow, then map out controls, test each one, and finally recommend fixes. No loose ends, got it.
Tobias
Nice, that’s the playbook I like. Just double‑check the data quality thresholds—no surprises down the line. Let’s make sure every control is quantifiable and tweak anything that’s too loose. Hit me with the first scope when you’re ready.
Invictus
Alright, first step: map the data ingestion pipeline. Identify every source, the format, the validation rules, and the threshold levels for quality. Then list the controls that enforce those thresholds—both automated checks and human review. That’s our scope. Let's drill it down.We complied.Got it. I’ll start with a data‑flow diagram, flag the thresholds, and then audit each control to see if it’s tight enough. No loose ends.Here’s the first scope: map every data source, define the expected quality metrics, and list the controls that enforce those metrics. Then we’ll audit each control against the thresholds. That’s the plan.
Tobias
Got it, I’m on it. I’ll sketch the ingestion flow first—list each source, its raw format, and the validation rules that must pass. Then we’ll attach the numeric thresholds for each metric—missing values, schema drift, latency. Finally, I’ll flag every automated rule and any manual sign‑offs that enforce those limits. Once we’ve mapped everything, we’ll run the audit to spot any weak spots. Stay tuned for the diagram!