Kyūdō vs. Traditional GRC
The difference between Kyūdō and traditional GRC is architectural. Traditional GRC platforms are systems of record: evidence is uploaded manually, assessments capture a point in time, and data lives in the vendor's cloud. Kyūdō is a system of proof: it runs inside your own Azure tenant, converts security signals into evidence continuously, and connects every compliance entity in one Compliance Graph.
This page compares the two models category to category. For the full definition of the newer model, read what an AI-native GRC platform is. For named product comparisons, see the compare hub.
Six dimensions, two architectures
Each row contrasts the traditional operating pattern with the equivalent in Kyūdō. Neither column names vendors; the comparison is between models, not products.
| Dimension | Traditional GRC | Kyūdō |
|---|---|---|
| Evidence collection | Manual uploads: screenshots, exports, and email attachments gathered by hand | Automated Microsoft-native evidence converted from Defender XDR, Sentinel, Purview, Entra ID, and Azure Policy signals |
| Assessment model | Point-in-time assessments that go stale between audit windows | Continuous controls monitoring: status recalculates as signals arrive |
| Data model | Disconnected controls, risks, policies, and vendor records in separate modules | Connected Compliance Graph: controls, risks, policies, vendors, evidence, and frameworks reference each other |
| Working surface | Spreadsheet-heavy workflows exported for tracking, review, and sign-off | AI-assisted governance workflows with citations, confidence scores, and human review below threshold |
| Integrations | Generic connectors that pull summaries on a schedule | Native Microsoft signal ingestion, plus AWS, Google Cloud, and Oracle Cloud signals |
| Hosting | Vendor-hosted SaaS: compliance data lives in the vendor's cloud | Customer-hosted Azure deployment via Azure Managed Applications, private endpoints only |
The monitoring row is the pivot: once evidence updates itself, every other workflow changes shape. See continuous controls monitoring for how that works in detail.
When traditional GRC is still fine
Not every organization needs continuous proof. If your compliance scope is small, your audits are infrequent, and your infrastructure does not run on Microsoft services, a lightweight traditional tool or well-kept spreadsheets can serve you adequately. Kyūdō's advantages compound with evidence volume, framework count, and the depth of your Microsoft estate. If those three are low, the simpler tool may be the right tool.
If they are growing, the economics shift quickly: all-inclusive pricing across three tiers replaces the per-module and per-integration fees that traditional platforms accumulate.
Compare against your own estate
The clearest comparison is your own tenant producing its first evidence. Deploy inside Azure and see the difference directly.
Questions, answered
The main difference is architectural. Traditional GRC platforms are systems of record: teams upload evidence manually, assessments capture a point in time, and controls, risks, and vendors live in disconnected modules. Kyūdō is a system of proof: it deploys inside the customer's Azure tenant, converts Microsoft security signals into evidence continuously, and connects controls, risks, policies, vendors, and frameworks in one Compliance Graph.
Kyūdō is a full GRC platform, covering controls, evidence, risk management, policy lifecycle, vendor risk, AI governance, and a Trust Center, so it replaces a traditional GRC tool rather than supplementing one. Organizations typically migrate framework by framework, using the Secure Controls Framework crosswalk to map existing controls into the platform.
Sometimes. If an organization has a small compliance scope, no meaningful Microsoft estate, and infrequent audits, a lightweight traditional tool or even structured spreadsheets can be adequate. Kyūdō's advantages compound where evidence volume is high, multiple frameworks apply, and Microsoft security services already generate the underlying signals.
Most traditional GRC platforms are vendor-hosted SaaS, so compliance data sits in the vendor's cloud. Kyūdō deploys through Azure Managed Applications inside the customer's own Azure tenant, with private endpoints only and no cross-tenant data plane. Evidence, policies, and AI inference on Azure OpenAI Service all stay in the environment the customer controls.
AI features added to traditional GRC tools typically summarize text without verifiable grounding. Sensei AI Advisor retrieves deterministically from the Compliance Graph, cites the source nodes behind every answer, attaches a confidence score, and routes low-confidence queries to human review. The AI is agentic with human-in-the-loop, not a detached chat window.
No. Existing controls map into Kyūdō's unified catalog through the Secure Controls Framework crosswalk with STRM semantic mapping (NIST IR 8477), which relates them to 80+ frameworks. Prior control implementations carry forward; what changes is how evidence for those controls is collected and kept current.
Looking for more? See all frequently asked questions.