USE CASE
Your AI took an action. Can you replay it?
A regulator asks why the AI made a decision. Your team digs through prompts, model versions, and config files. The answer takes weeks. The next regulator asks tomorrow.
npayload records every AI decision with the model, the inputs, the reasoning chain, and the outputs. Hash chained. Replayable. The audit your regulators ask for, ready in seconds.
WHAT THIS LOOKS LIKE
Six audit asks your AI stack is not ready for.
Modern regulators ask for explainability at modern speeds. Each one below is a question your AI stack should have the answer to before they ask.
Your apps
right now
Decision reasoning
Why did the AI choose this action
Model version
Which model ran, when, on what
Prompt audit
What prompt did this answer come from
Data lineage
What inputs informed the decision
Guardrail trace
Which policy checks fired
Disparate impact
Did decisions vary across protected classes
Every question is a moment your compliance team should answer with a query, not a project.
WHICH NPAYLOAD WEDGES
Two wedges. AI you can prove.
Primus records every decision with reasoning. Pipes records the workflow every row took.
Primus
Every AI decision on the audit ledger with reasoning, model, inputs, outputs. Replay any action exactly.
See PrimusPipes
Every row's workflow auditable. Models, prompts, rules, decisions all recorded.
See PipesEvents
The audit fabric underneath. Tamper evident. Cross region. Multi year retention.
See EventsONE AUDIT ASK, END TO END
Regulator asks at 9:00. Proof delivered by 9:00.1.
What used to be a two week audit project becomes a query.
Regulator asks
Email arrives requesting reasoning for 47 AI decisions.
Query ledger
Compliance queries the audit. Hash chained records pulled.
Reasoning attached
For each decision, the reasoning chain, model, inputs and outputs attached.
Disparate impact check
Aggregate analysis shows distribution across protected classes.
Proof delivered
Compliance hands the regulator a signed export.
Three flavors of AI audit.
Each one a regulator pleasing answer.
Individual decision replay
One AI action, full reasoning chain, model and inputs, replayable exactly.
Disparate impact analysis
Aggregate AI decisions across protected classes. Bias surfaces in the ledger.
Model version compliance
Which model ran on which data when. Required for many regulatory frameworks.
What teams ask before they ship.
Direct answers.
"Our prompts and models are our IP."
Per access role for the ledger. Compliance can prove decisions. Engineers can debug. Competitors cannot see your prompts.
"This is going to blow up our storage."
Tiered storage moves cold audit records to cheaper layers automatically. Compliance gets full history without enterprise tier cost.
"We use a vendor LLM."
We record the call, the response, the model version. Vendor model decisions become as auditable as your own.
Use case questions.
Your AI takes actions. Make sure you can prove them.
Wire one AI decision flow through npayload today. Run your first audit query this afternoon.
Join the waitlist.