We begin with the buyer's actual questionnaire and trace every AI-specific answer to a system, policy, contract, or named operating practice. That means following data from the user interface through prompts, retrieval, model providers, tool calls, logs, support systems, and deletion workflows. An answer is not treated as complete because a policy says the right thing; it must match the architecture that is running and identify where the supporting evidence lives.
Enterprise-Ready AI Security
The AI security questionnaire is stalling the deal. Turn your answers into reusable evidence.
AI compliance consulting for SaaS teams facing enterprise security questionnaires. Map controls to evidence, fix gaps, and reuse every approved answer.
Book a 30-minute consultation
30 minutes. No deck. Leave with a clear next step.
System-level interventionProduction-shaped diagnosisInspectable verification
The production trigger
Recognize the failure before naming the service.
Turn one active AI security review into a reusable control-and-evidence pack.
Your SOC 2 answers passed. Then the buyer added questions about model providers, agent audit trails, tenant isolation, embeddings, and human review. The answers exist across Slack, code, vendor dashboards, and one engineer's memory.
Trigger detail 1This service turns those answers into a standing pack your team can reuse, with the implementation work required to make each claim true and auditable.
Trigger detail 2System diagnosis
Find where the failure actually lives.
The visible symptom is rarely the whole problem. The first pass follows it through the production path until the controllable boundary is clear.
The review separates three kinds of gap that are often mixed together: an existing control that has not been documented, a documented claim that lacks durable evidence, and a material control that is not implemented. This distinction matters to the buyer and to your engineering team. It prevents a questionnaire exercise from quietly becoming an undefined security program, while still exposing the small number of technical changes required before an answer can be made confidently.
We also determine who can maintain the pack after the engagement. Model providers, embedding stores, subprocessors, retention settings, and agent permissions change faster than annual compliance cycles. If there is no responsible team, source of truth, and refresh trigger for each answer, the pack will become stale. This engagement fits teams with a live enterprise review and access to engineering, security, legal, and vendor records; it is not a substitute for an auditor or legal opinion.
The intervention
Change the critical path, not the surrounding theatre.
Each workstream targets a different failure boundary. Together they connect product behavior, infrastructure, controls, and verification.
Architecture and data-flow inventory
Document model calls, retrieval paths, tenant boundaries, tool execution, human-review points, and the systems that receive prompts or outputs. The inventory records data classifications, regions, retention behavior, encryption boundaries, and subprocessors. Ambiguous diagrams are resolved against configuration and code so the final response describes the deployed product rather than an intended future state.
Control-to-evidence mapping
Map buyer questions and selected framework controls to concrete artifacts such as access policies, audit events, test output, configuration exports, incident procedures, and vendor agreements. Each response records the evidence location, responsible team, review date, and condition that should trigger a refresh. Missing evidence is logged separately from missing implementation so the remediation queue stays actionable.
Priority control implementation
Implement the narrow technical gaps that block an accurate response, such as redacting sensitive prompt data from logs, recording agent actions, enforcing tenant-aware retrieval, or tightening provider configuration. Changes stay tied to the active review and acceptance criteria. Broader governance, certification, and policy programs remain explicit follow-on work rather than being smuggled into the intervention.
Reusable response system
Convert approved answers into a response library organized by topic, control, and product surface. The system includes short buyer-facing responses, deeper technical notes, evidence links, and approved caveats where the answer depends on configuration or contract terms. Your team can reuse the material without copying an old questionnaire and guessing whether its claims are still current.
Inspectable changes
See what changes in the system.
- SIG, CAIQ, and HECVAT-mapped AI security standing pack
- Agent-action audit trail review and implementation plan
- Tenant-isolation review for multi-tenant RAG
- PII and PHI handling audit across logs and embeddings
- Model-provider risk memo and DPA or BAA decision record
- AI subprocessor list with evidence links and review responsibility
- Reusable response library for future questionnaires
Engineering judgment
The decisions that determine whether the change holds.
Claim strength and scope
Decide whether each answer can be stated as a universal product control, a tenant-specific configuration, a contractual option, or a planned remediation. Stronger wording is not automatically better. The goal is language that survives technical diligence because its scope, exceptions, and evidence are clear to both the buyer and the people who operate the system.
Evidence system of record
Choose where durable evidence should live and how questionnaire responses link to it. The answer may combine your GRC tool, repository, ticketing system, cloud logs, and vendor records. We avoid creating a parallel evidence store that only one consultant understands, and we define access controls so sensitive artifacts can be reviewed without being broadly exposed.
Refresh and exception policy
Define which changes require an answer review: a new model or region, altered retention, a new subprocessor, expanded tool permissions, or a significant incident. We also define how temporary exceptions are recorded and retired. This turns the standing pack into an operating asset instead of a snapshot that silently diverges from the product after the next release.
Strong fit
- You have a live AI product and an enterprise questionnaire in motion.
- Your AI answers are scattered across people, code, and vendor dashboards.
Probably not the right fit
- You are pre-seed and have not sold to an enterprise buyer yet.
- You already have a mature GRC program that includes AI controls.
Scope, timing, and ownership
Know the commercial shape before the call.
A bounded engagement with a service-specific delivery sequence, an agreed price, and artifacts that stay under your control.
Day 1
Evidence map
Review the questionnaire, architecture, vendors, data flows, and current controls.
Day 2
Control gaps
Map gaps across SIG, CAIQ, HECVAT, NIST AI RMF, and buyer-specific questions.
Days 3-4
Pack and implementation
Write the standing pack and implement the highest-risk evidence gaps.
Day 5
Walkthrough and handoff
Review every answer, evidence link, owner, and refresh trigger with your team.
Typical fixed scope
Mid-four to low-five figures
Most engagements fall in this planning range. Your exact fixed price is agreed in writing after we review the production surface, access needs, and success criteria. The range is guidance, not a quote.
Commercial terms
No open-ended consulting meter.
- Fixed scope agreed in writing
- Fixed timeline agreed in writing
- Fixed price agreed before work starts
- Client-owned deliverables from day one
- No hourly meter or surprise overages
Client ownership
The implementation remains yours.
- Your repository
- Your infrastructure
- Your evals and evidence
- Yours from commit one
Book a 30-minute consultation
30 minutes. No deck. Leave with a clear next step.
AI Compliance
Questions worth settling before the call
Technical, commercial, and handoff questions answered before you book.
Turn the stalled review into evidence your buyer can inspect.
Bring the failing workflow, current evidence, and the constraints your engineers cannot ignore.
Book a 30-minute consultation
30 minutes. No deck. Leave with a clear next step.