Internal compliance

Speed up and expand the scope of your GRC program with AI agents

Run your internal GRC and security program with a fleet of agents monitoring your core systems while your team focuses on mitigating the biggest risks.

THE PROBLEM

People need to prioritize the risks they can monitor. With AI, you can do it all.

Before the advent of the AI agent, security and GRC teams had no choice but to approximate. The time required to look at everything going on in the business was too much. Now you can orchestrate a fleet of agents to look over every decision and system.

Best-guess answers to your customer questions

With limited resources, your GRC and security teams can’t be up to date with what you do internally. This leads to delays and inconsistent commitments that come to bite six months later.

Findings you didn’t know about and can’t defend

If you are forced to approximate, you are reduced to hoping internal or external auditors don’t find those areas you haven’t covered.

Fitting what you do to the platform you use

Every business is unique, but GRC tools often force teams to fit their processes and controls to the data model of that platform. This leads either to gaps or months of work on the part of the team.

What changes

You get better when you have all the facts on hand

GRC and security teams can be proactive when they have the time and data they need to make better decisions.

Get right to the source of truth

Replace document collection with real data so you can navigate problems before your customers start asking questions.

Prioritise where to invest time

Work on what the business really needs by modeling your customers, regulators, requirements and data on Atlas.

Always be audit-ready

HelmGuard’s agents have already thought about your next audit and have the evidence ready to send.

Give your GRC team the coverage it's never had. Get started within days.

HOW IT WORKS

Answer customer questions using Atlas

1. Agents on Atlas draft answers using the program you’ve built with us

2. Approved answers get reused where appropriate

3. Uncertainty is quantified based on retrieval and source reliability

4. Each iteration is used to further refine where you need to invest next

1. Agents on Atlas draft answers using the program you’ve built with us

2. Approved answers get reused where appropriate

3. Uncertainty is quantified based on retrieval and source reliability

4. Each iteration is used to further refine where you need to invest next

1. Agents on Atlas draft answers using the program you’ve built with us

2. Approved answers get reused where appropriate

3. Uncertainty is quantified based on retrieval and source reliability

4. Each iteration is used to further refine where you need to invest next

Case STudy

A global technology company replaced questionnaires with HelmGuard agents

A global healthcare tech company runs 40 products across 20 countries on one assurance foundation with newly acquired companies plugging into the same process.