AI Systems
Evidence for systems that decide.
As models, agents and retrieval pipelines take on consequential work, the organisation remains accountable for what those systems knew and why they acted.
Use cases
Where Safe Haven is intended to apply.
Automated Decision Systems
Reconstruct why an automated decision occurred.
AI Agents
Follow agent actions and tool calls across workflows.
RAG Systems
Identify which source content was supplied to a model.
Regulated AI
Maintain evidence for governance, compliance and investigation.
Human + AI Decisions
Capture where responsibility transitioned between system and person.
Model Migration
Compare outcomes before and after model changes.
Data Corrections
Identify historical decisions potentially affected by incorrect data.
What gets captured
Capture the context, not simply the output.
Model
Provider, model family, exact version or checkpoint where available, and configuration.
Prompt
System prompt, user prompt, template and template version.
Knowledge
Documents, vector results, database queries and source records.
Data
Relevant business data with its temporal state.
Agents
Agent identity, task, hand-offs and workflow metadata.
Tools
APIs, functions and external services invoked.
Policy
Business rules, guardrails and regulatory controls active at the time.
Identity
Person, service or AI process initiating the activity.
Human Oversight
Approval, escalation, rejection or override by a person.
Decision
Model output plus the actual downstream business action.
Integrity
Hashes, signatures and evidence-chain verification.
Replay
Three questions, three forms of replay.
Recorded Replay
What actually happened?
Display the evidence captured around the original AI event without rerunning it.
Historical Reconstruction
What did the system know at that time?
Reconstruct relevant data, policy, model, prompt, retrieval and knowledge state.
Counterfactual Replay
What would happen using what we know now?
Re-evaluate historical decisions using corrected data, changed policy or a different model.
Exact computational reproducibility may depend on the continued availability and deterministic behaviour of external models and services. Safe Haven therefore distinguishes recorded evidence from computational re-execution.
Logs tell you that something happened. Safe Haven is designed to reconstruct the state in which it happened.
Strategic engagement
Government, banking or technology stakeholder?
We are currently developing the Safe Haven architecture and exploring potential pilot, policy, infrastructure and funding partnerships.