01 Horizon scan
Start here
The AI rules and policies that apply to you, market by market, dated and cited to the clause.
You get: Horizon scan, Impact assessment, Timeline by market.
AI governance, risk and compliance
See every AI system. Govern every decision.
Start with the AI rules and what they ask of your inventory. Then run the priority workflows on it. Built with your experts, on your infrastructure, signed off by your people.
Ask Ray the questions your board asks
- Which new AI rules hit us first, and where? Each rule dated and cited, market by market, tied to the systems it affects.
- What do the rules ask our AI inventory to hold? Each clause matched to the inventory field, template or check that shows you meet it.
- Which AI systems lack an owner, a risk rating or an oversight level? Each system's owner, risk rating and oversight level, with the gaps flagged.
- Which AI systems carry the most risk, and what do they need? Each system rated against your risk taxonomy and the rules; your expert confirms the tier and the controls.
- What does the board need to see this quarter? The quarterly pack drawn from the inventory, with sources cited.
A governance system built on your evidence
From signals to a signed record. The right method for each step, inside your Microsoft 365 and databases.
Start with the rules. Verify how you meet them.
Find the rules that apply to your firm, then build the record that shows you meet them.
02 AI inventory requirements map
Start here
What the AI rules in your markets ask your inventory to hold, clause by clause and field by field.
You get: Requirements map, Gap report, Templates by clause.
03 AI inventory
Each AI system, built in-house or bought, with its owner, purpose, risk rating, oversight level, explainability and kill switch, attested by its owner.
You get: AI inventory, AI risk register, Attestation report.
04 AI risk assessment
Each AI system rated against your risk taxonomy and the rules that apply: its risk tier, the harms it could cause and the controls it needs, signed off by its owner.
You get: Risk assessment, Risk tier and harms, Control plan.
05 Board reporting packs
The quarterly board pack and monthly exceptions note on AI, drawn from the inventory, with sources cited.
You get: Board pack, Committee paper, Exceptions note.
Each workflow can be bought and run on its own.
Two ways to work with Rayify
AI governance on your infrastructure
Ready-built workflows for the horizon scan, the requirements map, the AI inventory, AI risk assessment and board reporting. Configured for your firm.
Hands-on labs to solve your top priorities
Briefings, governance labs and hands-on builds for technical and non-technical teams.
Cloud, hybrid or local
Cloud
Everything runs in Rayify’s cloud
Hybrid
Sign-in in our cloud, a sealed engine and your data in yours
Local
The whole system on your premises
In each option: a sealed, versioned system that we deploy and operate, and an audit trail that belongs to you.
Build your team's capability to own and run priority workflows
- Non-technical: AI productivity, Claude and Copilot connectors, agentic governance
- Technical: sub-agent orchestration, safety guardrails and data privacy for agentic systems
- Control functions: test model outputs, challenge a vendor claim, work from the inventory
Bring one use case to a pilot
Tell us what you need to stay on top of. We scope a pilot around one real use case, in your markets, with your experts.
What happens next
- We reply within 2 working days.
- We scope the pilot to one use case in your markets.
- Your data stays yours: under NDA, and never used to train AI models.
Frequently asked questions
What data sources do you have access to?
We work from four kinds of source. The rules and guidance in each market you operate in, with the date each one applies from. Your own register of AI systems, and the policies and standards behind it. Your vendor contracts and the vendors’ release notes. And usage exports from the AI tools your staff use, such as Claude and Copilot, read on your own machines. Every finding is attributed to its source, so you can check where any line comes from. For ongoing work we can connect the tools your team already uses, such as Microsoft 365, your identity provider and procurement, so the register stays current inside your existing workflow rather than alongside it.
What does an engagement actually look like?
It starts with the question your board or your regulator is asking, such as what AI the firm runs, or which rules apply from when. For a first engagement we run a short scoping session to agree the markets and teams in scope. We then start from an example template that gets you most of the way, adapt it to your firm and have Rayify’s AI risk experts sign it off, and your owners attest their own records. You leave with a register, a clause compliance map and an evidence pack you can take to your regulator. For your control functions, risk, compliance and audit, Labs teach your people to evaluate AI and challenge what it produces, so they can run the work themselves afterwards.
Who sees our inputs?
Engagements run under an NDA by default. You choose where the system runs, in our cloud, hybrid or on your own premises, and usage exports are read on your own machines, so they need not leave them. We never use what you give us to train AI models. Your documents are encrypted and private to your organisation, never pooled or shared, and access is limited to the team on your engagement, for that work only. The audit trail belongs to you.
How is this different from Claude, Gemini or ChatGPT?
Copilots are useful for everyday work. Governing AI across a regulated firm needs a record of each use, mapped to the rules and signed by its owner.