I answer the questionnaires that hold it there — SIG Lite, CAIQ, or whatever spreadsheet the buyer's risk team invented. Every answer cited to a document you already have. Every gap returned as a question, not a guess.
Custom risk spreadsheet sent by enterprise buyer. Ingested under mutual NDA.
"Questionnaire asks about hypervisor boundaries. Our architecture uses Kubernetes pod isolation + Nvidia MIG."
Policy says 30 days; vector DB configuration shows 14 days snapshot cycle.
Returned with full cell comments. 100% cited. Deal closed.
Your customer asks whether production data is encrypted. You answered that last month. The answer is in a policy, but the policy is fourteen pages long and nobody remembers which paragraph.
Then the questions get specific: whether your subprocessor list matches your data-flow diagram, whether a pen-test finding is closed, whether the scope of your SOC 2 actually covers the product they are buying.
The spreadsheet is not hard because the questions are new. It is hard because every answer is a representation your company has to stand behind.
Send me one questionnaire you have already completed. I answer it blind from your documents, then compare my work with the answer your team approved.
SOC 2 Type II reports, ISO 27001 policies, pen test summaries, AWS architecture diagrams, and previous questionnaires. They stay under NDA, in your dedicated client vault.
When buyers ask about multi-tenant GPU isolation or vector encryption, cite your AWS spec, Kubernetes network policies, and pen test remediation in one cohesive response.
If an answer isn't supported by existing evidence, it is returned as a targeted question, not an automated guess. You get the exact document title that would solve it.
Rowan Sterling brings 11 years of infrastructure security experience. Tooling indexes and drafts; a human decides what represents your company.
Zero retention on external models • Isolated client namespace
Policies, architecture documents, audit reports, pen tests, previous answers, and operational records become a cited evidence store for the next questionnaire.
@Rowan Sterling matched AWS Multi-Tenant GPU Isolation in Notion & AWS Spec. Cited hypervisor-free pod boundaries using Cilium eBPF network rules.
Run via local Ollama/Mistral endpoint or zero-data-retention VPC proxy. Your policies never leave your hardware boundary.
Green, amber, and red make the remaining work obvious. Every source stays attached to the answer it supports.
"Describe tenant isolation mechanisms. Are customer workloads logically separated and how is cross-tenant memory access prevented?"
"Customer training and inference workloads run in mutually isolated Kubernetes namespaces with Cilium eBPF network segmentation (zero egress between tenants). GPU compute is sliced using hardware-enforced Nvidia MIG partitions with independent memory controllers, preventing any cross-tenant memory bleeding."
Source: AWS-ARCH-2025-V2.pdf §4.2 (Last reviewed 18 Jan 2026). Cross-referenced against Schellman SOC 2 §CC6.1 and Bishop Fox Pen Test §3.1. Verified by Rowan Sterling.
Every tool in this category advertises how much it automates. None of them tell you how often they're confidently wrong. Across 16 questionnaires, run blind against answers the client had already approved:
Questions genuinely supported by the evidence set, with exact document paragraphs and review dates.
"An unverified claim isn't invented. It comes back as a targeted question with the exact policy needed to resolve it."
The number that matters. I report it so you know how much review your team still owes each answer.
An answer with no supporting document comes back as a question, never a plausible sentence with nothing behind it.
That is a limit on volume and an advantage on judgement.
UK and EU B2B software companies, roughly seed to Series B, selling into enterprise or regulated buyers — especially where the infrastructure does not fit a standard answer.
ML training, simulation, HPC, GPU tenancy, research compute, and complex multi-tenant SaaS.
11 years in infrastructure security, including ML infrastructure, multi-tenant GPU clouds, and enterprise B2B SaaS architectures. I have written answers under deal pressure and reviewed answers written by people who had never touched the system.
The tooling drafts and cites. I decide what is actually true about your estate.
I do the review. You make the representation to your customer.
Policies, audit reports, pen test summaries, architecture docs, and your last few completed questionnaires. NDA first, over a channel I name — not an upload form.
Every claim is indexed to its source document and that document’s review date. This happens once. It is what makes the fourth questionnaire faster than the first.
In whatever shape it arrived — SIG Lite, CAIQ, a bespoke spreadsheet, or a buyer portal export.
Same tabs, same columns, same formatting. Green where the answer is cited and current, amber where the source is aging, red where I need something from you. Sources sit in the cell comment.
Your approved answers become evidence for the next one, and the next questionnaire costs less.
Most clients start per-questionnaire and move to retainer once they have seen what the second one costs compared with the first.
One completed questionnaire and one report showing what your evidence genuinely supports, what it does not, and where my draft disagreed with your team.
Straight answers about the person, the tooling, and where responsibility sits.
Yes, as disclosed tooling for indexing, retrieval, and first drafts. It does not decide what is true. I review every answer against its source before it reaches you, and unsupported claims come back as questions.