Ruleguard FAQs

Every agent operates within configurable boundaries - permitted actions, prohibited actions, escalation triggers and approval gates - all version-controlled. You set the level of autonomy per workflow and per step. See how this works on our Platform page 

Oversight is a dial, not a switch. Three modes: Full Review (every output reviewed - for initial deployment and high-risk tasks), Exception-Based (humans review only flagged items), and Autonomous (agent runs independently with periodic audits, for mature, well-understood tasks). You can dial it up or down at any time. See how this works on our Platform page 

Yes. Every agent decision is logged with its reasoning, the sources it referenced, and the rules it applied - designed to meet supervisory expectations for transparency in AI-assisted decision-making. 

Immutable. Every decision, every data source consulted and every output is recorded and nothing is overwritten or lost. When a regulator or internal auditor asks why a decision was made, the full chain of reasoning is available instantly. See how this works on our Platform page

The platform is built around the themes supervisors emphasise: data transparency and lineage, continuous control monitoring, outcomes-based assurance, explainable AI, operational resilience (impact tolerances since March 2025), and proactive risk management. See how we help you keep pace on our Regulatory Change Management page

Ruleguard is compliant with ISO 42001, the international standard for responsible AI management — so how agents are trained, deployed and monitored sits within a formal AI management system you can point to when regulators ask how AI is controlled. Read more about our approach on the Why Ruleguard page

The platform uses frontier AI models within a framework purpose-built for compliance, and supports a range of models and deployment options so you can match your own AI policy, risk appetite and data-residency requirements. Read more about our approach on the Why Ruleguard page

Agents reference your authoritative sources — your policies and procedures — not generic training data. This is structured through four context layers: organisational context, constraints (boundaries), intent (the outcome a rule serves, which cuts false positives), and modular specification. The aim is accuracy grounded in your documents, with reasoning shown. See how this works on our Platform page

When your policies update, agents reflect the change immediately. On the regulatory side, agents continuously scan developments across jurisdictions, classify and prioritise them, and assess impact against your existing policies and controls. See how we help you keep pace on our Regulatory Change Management page 

Yes, every task sharpens accuracy and efficiency, and agents become more attuned to your organisation. Your data is never used to train shared/base models but references your historical usage patterns and preferences securely in a single-tenant data model. See real examples on our Case Studies page

Yes — Ruleguard holds ISO 27001 (information security) and is compliant with ISO 42001 (responsible AI). Want the full certification pack? Get in touch

The platform supports a range of frontier cloud models and on-premises deployment, so you can meet your data-residency requirements. Support for on-premises models varies by region, please enquire for details. See our Data Centers page for full hosting details

No, this is a fundamental design principle. We use a secure single-tenant data model which isolates your data both logically and physically. Your data is never used to train models or shared with other clients and the agents on your account only access your data and usage patterns. See our Data Centers page for more on how your data is hosted and secured.

Ruleguard uses a strict single-tenant data architecture, encrypts data in transit and at rest, and has a wide range of enterprise-grade infosec and cyber security features. We use Microsoft Azure data centres with the most robust security certifications in the world. See our Data Centers page for more.

Yes, Ruleguard is ISO 27001 certified, conducts regular pen testing, and is well-versed in responding to the most rigorous information security questionnaires from global banks and asset managers. Ask your account team for our latest security pack — get in touch.

Ruleguard supports a range of integration methods including APIs, webhooks, Zaps, and CSV bulk integration. Agentic integration is via the platform's MCP server, which gives authenticated, permissioned access governed by the same audit and permission controls as the rest of the platform — and you control exactly what is shared. See our Integrations page for more 

No. Ruleguard works as a standalone platform out of the box. Integration is available when you're ready, at your pace. We do offer historical data import services as part of implementation, meaning that you can give your Ruleguard agents access to your relevant data stores from day one, if your use-cases demand it. See our Integrations page for more 

Through an MCP server, in two directions: your own agents/tools can be given secure access to Ruleguard's compliance data, and Ruleguard agents can reach out to external systems to pull in additional context — without re-engineering your infrastructure. See our Integrations page for more

Automated feeds via API integrations, webhooks and system logs flow in for real-time data, alongside manual inputs (attestations, checklists, approvals) for processes needing human judgement — all in one unified dashboard. See our Integrations page for more 

Very little. Our in-house implementation team handles end-to-end deployment and implementation and typically we only need a few simple tasks from your IT team including IP whitelisting, SSO/identity (SAML/OIDC), and support for any systems integration work required for the set up. See a recent implementation case study

Very little. Our in-house implementation team handles end-to-end deployment and implementation and typically we only need a few simple tasks from your IT team including IP whitelisting, SSO/identity (SAML/OIDC), and support for any systems integration work required for the set up. See a recent implementation case study

The platform's maturity journey explicitly includes an Adoption stage — embedding agents into daily operations so teams work with them, not around them — followed by management, governance and measurable economic benefit stages. See how this plays out in practice in our Case Studies 

Start in Full Review mode so every output is checked, then move to Exception-Based and ultimately Autonomous as each agent builds a track record — entirely under your control, per workflow and per step. We recommend 10-12 weeks of agent testing and feedback to reach a steady run-rate of agent productivity and quality. See how this works on our Platform page

We have an in-house implementation team covering all implementation, configuration, data import, project management, and agent training services. Our customer service team is always on-hand following full go-live and we run a 24/7 global helpdesk service. Want to talk through what onboarding looks like for your firm? Get in touch

Ruleguard uses value-based pricing related to the number of regions, legal-entities, and compliance use-cases that our client benefits from. Pricing is tailored to your firm — speak to our team for more information.

Ruleguard clients experience ROI in two main ways: firstly by reducing the time and cost required to operate risk and compliance workflows given the automation provided by Ruleguard agents, and secondly by an acceleration in the time-to-market and time-to-approval resulting from the auditable compliance posture that Ruleguard delivers. Read more on the real ROI of GRC 

Ruleguard has been trading since 2013, has over 50 blue-chip financial services clients globally, and is backed by one of the largest UK venture capital investors. We pass the rigorous financial checks demanded by some of the largest banks in the world. Learn more about Ruleguard or see our Case Studies