DNSFilter is MSP-native: sites, roaming agents and per-client organizations under one console. That structure makes it the cleanest source in this series for producing separate, client-labeled AI audits at scale.
The core discipline: one export per client organization, one upload per client, one labeled report per client. Never merge tenants.
Pull each client's query log CSV for the same 30-day window. Same window across clients is what makes your cross-client benchmarks honest later.
Run each file separately and enter the client's name at run time. The label prints on every page of that client's PDF, which is what makes it a deliverable instead of an internal artifact.
PDF to the client with your recommendations, CSV into your PSA notes, next quarter's run into the calendar. The commercial framing lives on the MSP page.
Separate runs are also the data-handling answer: each client's evidence, retention and deletion stay independent, which is the sentence your MSA reviewer wants to read.
The query log CSV carries the domain, the requesting identity and the policy result. That is the whole recipe.
Agents and sites become sources in the report. The roaming sales laptop transcribing calls off-site is the classic line-five finding.
An eight-person MSP runs the same 30-day export for three very different clients. Sample data; the spread is the lesson.
9 AI tools. Chatbots plus a document summarizer, nothing abusive.
Finding: the summarizer's training terms are unstated, and tax documents are the workload.
Action: enterprise alternative sanctioned, consumer domain blocked, client signs the quarterly cadence.
6 AI tools, but one is a dictation app on two roaming laptops, terms silent on training.
Finding: privileged audio potentially processed by an unvetted vendor.
Action: immediate block plus a vetted legal-transcription tool; the report PDF goes to the managing partner same day.
22 AI tools, heavy image and copy generation, two flagged training-by-default.
Finding: product photography edited through consumer tiers, client IP in the uploads.
Action: team plan migrations, and the MSP's first paid "AI governance" retainer conversation.
Same export shape, three different risk stories. That spread is why per-client reports beat one merged view: each PDF speaks that client's language to that client's board.
After a quarter of consistent windows, your client base becomes its own reference data. Three comparisons clients pay attention to:
The e-commerce brand's 3.7 versus the law office's 3.0 reads differently once clients know the peer range. Nobody wants to be the outlier without a reason.
The percentage of tools that train on data by default or opt-out. A client above your book's median gets the terms-review pitch with evidence attached.
Clients with a real approved list trend toward high sanctioned share within two quarters. The laggards are your governance-retainer pipeline.
| Report section | With a DNSFilter CSV |
|---|---|
| Header and scope | The client's name as entered at run time, on every page. |
| Summary tiles | Full totals per client: tools, high-risk, training exposure, abusive, unsanctioned. |
| Tool table | Every matched domain with category, risk, sovereignty and dated training verdicts. |
| Per-source table | Agents and sites with tool counts and hits: which office, which roaming laptop. |
| Sanctioned split | That client's approved list against their observed traffic. |
| CSV + PDF | The PDF is the deliverable; the CSV feeds your PSA and their risk register. |
Each upload is read once and discarded. Reports live 90 days in your account and can be deleted per client, earlier on request. Put those two sentences in the engagement letter.
Open the sample evidence pack with the client-label header, the tool table and the per-source breakdown. Attach it to your next QBR agenda and let it sell the assessment.
The scenario's morning used three full audits. Ways to cover that, from lightest to standing.
$66 a report, no subscription. Right for testing the motion on three friendly clients, exactly like the scenario.
$60 a report. An engagement season's inventory for a small book of clients.
Technically yes, practically no. Merged tenants produce one blended report, which is useless as a client deliverable and messy as evidence. One export per client.
The query log CSV per client organization over your window, keeping domain, agent or site, action and timestamp columns.
They improve it: device-level attribution and off-network coverage. Site-only clients still get full tool inventories with location-grain sources.
You enter the client's name when you run the audit; it prints on every page of that PDF. Labels are per run, so three runs mean three cleanly branded deliverables.
No. Each report is its own document from its own upload, in your account. Separate uploads keep evidence and deletion independent per client.
Hostnames from their own logs, matched against a register of 20,399 classified AI domains maintained daily. The methodology page is client-shareable.
The MSPs who convert audits into retainers wrap the report in three small artifacts of their own.
Your logo, three findings in plain language, three recommended actions with effort estimates. The client forwards this page, not the PDF, so it carries your brand.
The report's block/control/allow verdicts as a checklist the client can approve line by line in one meeting. Approved lines become your tickets.
From the second quarter on: "tools 22 to 17, training exposure 8 to 3, sanctioned share 20% to 74%". One sentence that renews the engagement by itself.
Benchmarks and trend lines die from sloppy inputs. These five habits keep the data honest across a client book.
Fifth habit: read each report against the client's own sanctioned list, not a generic one. Building that list is covered on sanctioned vs unsanctioned AI.
Pick three clients, pull three query logs, run three audits. The Tuesday-morning scenario is a repeatable play, not a story.
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