Every day, AI decides:
AI Makes Millions of Decisions Daily
And We Don't Always Know…
And when the auditor asks, can you prove it?
Why We Exist
To build a movement for accountable AI, ensuring AI is fair and that people have recourse when it fails, so that everyone affected by an automated decision can understand it, trust it, and challenge it.
Understand it
Why the decision happened.
Trust it
Evidence that the process was fair.
Challenge it
A route to review and recourse.
In plain terms: Regitech is the "black box flight recorder" for AI. We record decisions, preserve the evidence of why they were made, and give people a fair way to challenge outcomes they believe are wrong.
Six principles that follow from the Why
We record the decision, not just the policy
A policy document proves intent. Only an evidence trail proves what actually happened in a specific decision — which system ran, what disclosure was made, who reviewed it.
Modular and provider-agnostic by design
We are built to sit alongside the governance, content and case systems an organisation already runs — not to replace them, and not to lock a client to one model provider.
A human stays in the loop
Accountability is not automated away. Human review, override and escalation are recorded as first-class events, because a person must remain answerable for the outcome.
Dispute resolution is the starting point, not an afterthought
Regitech was founded from mediation and ADR practice. We design backwards from the moment a decision is challenged — because that is when evidence has to hold up.
Inspectable without being exposed
Detailed evidence stays private and access-controlled. Where tamper-evidence adds value, we anchor hashed references rather than publishing sensitive content.
We say what we can prove
Every capability on this site carries a status. Research is labelled as research. If we do not list it, we are not claiming it.
The operational gap we close
Most organisations have AI policies. Very few can answer these six questions about one specific decision, on demand, with evidence.
Four modules, not a universal platform
Deployed as a modular evidence layer with implementation support, so an organisation adopts only the parts its workflow needs.
Audit Readiness
When a third-party audit, regulator or court asks about one specific decision, reconstruct and export a chronological evidence packet on demand — instead of an archaeology project across logs, tickets and inboxes.
See it in the prototypeProvenance & Disclosure
Manifests, content hashes and disclosure records that capture what was AI-assisted, by which provider and model, and what was disclosed to the person affected.
See the architectureEvidence Orchestration
The workflow layer that links a decision or content item to the policy that applied, the technical controls that ran, and the record that was preserved.
See how it worksHuman Oversight & Dispute Workflow
Review gates, overrides, escalation and case handling — so a challenged decision has somewhere to go and someone accountable for answering it.
See dispute resolutionThe Problem: AI's "Black Box" Crisis
AI systems make decisions that affect people's lives every second. When you ask "Why did the AI make this decision?" — answers are often unavailable or incomplete.
Limited accountability mechanisms. Few effective appeal processes.
Insufficient proof of fairness.
Why Should Business Leaders Care?
$10.3B
Annual AI-related fraud reported by the FBI
€35M
Maximum fines under the EU AI Act per violation
67%
Americans concerned about AI-driven misinformation
$20B
Annual synthetic identity fraud losses worldwide
This Is Already Happening
$25.6 Million Lost in One Video Call
A finance worker joined a video conference with the CFO and several colleagues who authorized an urgent wire transfer. Every person on the call was AI-generated — deepfakes that looked and sounded exactly like real executives.
The money is gone. There was no way to verify authenticity.
Skilled Writers Fired for Writing Too Well
Professional writers lost their jobs after AI detection tools wrongly flagged their human-written work as "AI-generated." Good grammar and punctuation became evidence of fraud — quality writing penalized by flawed algorithms.
Careers destroyed. Reputations damaged. Limited recourse available.
Leading AI Systems Chose Harmful Actions
Researchers tested 16 major AI systems with business goals. When ethical options conflicted with targets, harmful actions followed — including blackmail and data leaks — with some models showing rates as high as 96%.
Who monitors these decisions? Who sets the boundaries?
The Critical Gap
Current solutions are often too slow (manual audits taking weeks), too expensive ($50K–$500K per audit), or too incomplete (capturing outputs without the reasoning behind them).
The missing piece: Few solutions combine real-time monitoring with a legitimate process for challenging unfair AI decisions.
Built for the auditor
When a third-party audit arrives, the evidence is already there
Governance is moving from voluntary policy to verifiable proof — from Illinois’s annual third-party safety audits to EU high-risk enforcement. When an assessor sits down, they work through a checklist. These are the questions they ask, and what we capture as they happen.
Did a human have the power to veto — and did anyone use it?
Review gates, overrides and escalations are recorded as first-class events, not reconstructed after the fact.
Which system, provider and model made or assisted the decision?
Manifests capture the AI system, provider and model attached to each recorded decision.
What was disclosed to the person affected?
Disclosure records are held alongside the decision, so what was said — and when — is on file.
When the agent hit a boundary, what happened next?
Human handoff and escalation are captured as events, so the moment control passed to a person is on the record.
Can the whole chain be reconstructed months later?
Search, reconstruct and export a chronological evidence packet for one decision, on demand.
A clear boundary: we don’t audit or red-team your models. We make sure that when someone does, the evidence is already there.
Capability status
We Label What Is Built, What Is Being Validated, and What Is Research
A company asking to be trusted with accountability evidence should be accountable about its own maturity. So we publish it.
Built and available to configure in a design-partner pilot.
- Modular evidence workflow
- Document processing & structured extraction
- Redaction records
- Human handoff & escalation
- Audit-event capture
- Manifest handling & validation
- Evidence search & export
Working, but not yet independently or contractually proven.
- C2PA conformance
- Optional tamper-evident anchoring
- Public verification endpoint
- Licence-event monitoring
- Third-party detector integrations
Design and research work. Not a current product capability.
- JEPA reasoning-alignment layer
- Multi-agent swarm consensus
- Diffusion-model simulation
- Automated enforcement actions
- Scam-mitigation adjacency
We complement, we don't replace
Regitech is designed to work alongside the AI governance, GRC, privacy, model-risk, content-provenance and case-management systems an organisation already runs. We add the event-level evidence those systems were never built to hold — we do not ask a client to rip anything out.
What we do not claim
- A complete, end-to-end AI governance platform
- Detection of all AI-generated content
- Legal advice, certification or a guarantee of compliance
- A production-proven multi-chain blockchain system
- Prevention of phone or online scams
Status last reviewed: 4 August 2026. Capability labels are maintained by Regitech and reviewed before publication. Scope for any engagement is confirmed through technical discovery. Regulatory summaries on this site are for information only and are not legal advice. Ask us about a specific capability.
Provenance & Disclosure
Where content came from, and whether AI was involved
Evidence Orchestration
The decision record, captured as it happens
Human Oversight
Named accountability at the points that matter
Audit & Dispute
Evidence a regulator, a reviewer or the person affected can read
Four modules. Adopt one, or adopt all four — they are designed to work with the governance and case systems you already run.
Are You Ready to Lead in AI Accountability?
Regulatory deadlines are approaching. Organizations that act now will have the operational experience and competitive advantage that others will struggle to build under pressure.
Explore the Technology
See how the four modules fit together, what is implemented today and what is still in validation.
See How We Help
From pilot programs to full deployment, discover the path that fits your organization's needs.
Know Your Deadlines
California, Colorado, EU, DIFC — understand what regulations apply and when compliance is required.