Supercharge what you already use.

Siemserva by Senserva can stand alone, but does not have to. It works alongside whatever you already use, running an ongoing security review that spots and helps fix the high-priority issues. Plays nicely with everyone.

Stop building from scratch. Plug 650+ deterministic checks, remediation automation, and Senserva Trustworthy AI straight into the PowerShell, Maester, and Microsoft Zero Trust Assessment runs you already own, and bring in your own products and scripts too.

Building a product to sell? Use the SDK the other way, too. Pull Siemserva's findings, security graph, and validated remediation into your own application with the Siemserva libraries (DLLs) running behind the scenes, so your customers get deep Microsoft 365, Intune, Defender, and Entra ID security without you building a scanner.

How Siemserva plugs into what you already run Your PowerShell, Maester, the Microsoft Zero Trust Assessment, and your own product feed one security graph, which then drives the dashboard, six AI-enhanced reports, and the Claude MCP. Your PowerShell Maester Zero Trust Assessment Your product or scanner One security graph Local SQLite or Azure database Dashboard 6 AI-enhanced reports Claude MCP + your AI
Email us about the SDK

Get going quickly. Build for the long term. Built by a Microsoft security ISV: Senserva is a Security ISV of the Year finalist (2024 Microsoft Security Excellence Awards) and a Microsoft Intelligent Security Association (MISA) member.

Enhance any product you already have, fast

Point your existing scanner, script, or security product at the Senserva data model and it inherits deep, connected data and full agentic AI support, without building any of it yourself.

Most tools stop at a flat list of findings. Siemserva turns whatever you already produce into rich, queryable, AI-ready security intelligence. Write your results into the shared Siemserva database with SenservaWriter, or emit Senserva JSON from any output, and your data lands in the same graph as native scans. No Siemserva scanner or dashboard code is changed. It shows up in the dashboard, the six AI-enhanced reports, MCSB and CISA SCuBA compliance mapping, and the Claude MCP, automatically.

One command. Full SDK.
$ siemserva-win-x64.exe --sdk

Drops the full SDK: API reference, C# / Python / PowerShell samples, and the Senserva JSON wire format.

1. Write or emit

Call SenservaWriter from C#, or emit Senserva JSON (one object per line) from PowerShell, Python, or any language. Tag each row with a Source so your data stays separable from native scans.

2. Land in the graph

Your data joins one connected model: audit findings, graph nodes, and the edges between them, sitting next to identity, devices, apps, Conditional Access, patches, and CVEs.

3. Get AI for free

The dashboard, the six AI-enhanced reports, compliance mapping, and the Claude MCP tools all light up over your data, with no extra code to write.

Three layers, written together

Each finding is written as all three at once, the same shape as a native Siemserva finding, so nothing downstream has to know where it came from.

Audit rows
One row per finding in Audits and CurrentAudit, ranked by Severity, for dashboard and report visibility.
Graph nodes
Rich records in Node_* tables, the source the MCP and SDK query. CVE nodes carry the CVSS score, CISA KEV status, and full detail JSON.
Graph edges
Relationships in Edge_* tables so the AI can traverse, for example a device to its missing patch to the CVE that patch fixes.
Write your findings in a few lines
// C#: write audits, nodes, and edges into the shared database
using var writer = new SenservaWriter(databasePath, source: "MyProduct");
await writer.WriteAuditFindingsAsync(device, findings, tenantId, tenantName);
await writer.WriteDevicePatchDataAsync(device, patches, tenantId);

# Or pipe Senserva JSON from any tool, with no code at all
your-scanner | siemserva --reporter   # full reports + compliance

Read it back just as easily with SenservaClient in C#, the PowerShell module, or zero-dependency Python over the SQLite file, or our Azure shared cloud database.

The result: your existing product gains a deep security graph and agentic AI that works with any model in an afternoon, not a roadmap. See the unified security model it plugs into, or run it all from Claude over the MCP.

Open data you own, not a locked vendor cloud

Every finding, node, and edge lives in a standard, documented SQLite database on your machine, or in our Azure shared cloud database when teams need one model across many tenants. Query it, export it, and point any tool at it.

Siemserva keeps your security data open. There is no proprietary store and no cloud you have to call to read your own results. The graph is a plain SQLite file, or our Azure shared cloud database, with an open, documented schema, the same node and edge tables the dashboard and the AI read, so you can run ordinary SQL, build your own dashboards, feed a data warehouse, or hand it to the AI of your choice. Findings move in and out as Senserva JSON, a simple newline-delimited, camelCase format any language can read or write. Your data stays local and private, the way Senserva Trustworthy AI is designed to work.

Standard SQLite, or Azure
Open the same .sqlite file the dashboard uses with any SQLite tool, or run the same model as our Azure shared cloud database. No special driver, no API gateway, no waiting on a vendor.
Open, documented schema
The node and edge tables are documented, so you write your own queries and joins instead of reverse-engineering a black box.
Yours to export
Export to Senserva JSON, share a portable .senserva file, or read straight from C#, PowerShell, or zero-dependency Python.
It is just SQL
-- the same data the dashboard, the reports, and Claude read
SELECT Name, Severity FROM CurrentAudit WHERE Severity >= 375 ORDER BY Severity DESC;

No copy is hidden from you, and nothing is locked behind an API you do not control.

Integrations Examples

Anything that emits Senserva JSON lands in the same dashboard, the same six AI-enhanced reports, and the same Claude MCP tool surface.

Maester

Pester-based Microsoft 365 security tests by the Maester community. Failed tests land in Siemserva with severity, remediation, and compliance mapping already attached.

Microsoft Zero Trust Assessment

Microsoft's official ZTA pillar results land alongside Siemserva's own scans, with the same severity model, the same dashboard tabs, and the same HTML reports.

Your own PowerShell

Have audit scripts already? Emit Senserva JSON from any output and your findings land in the same graph as native scans, with AI analysis and Claude over MCP for free.