Security questionnaire automation that clears deals without the bottleneck.
Draft cited, confidence-scored questionnaire responses from approved evidence and route only uncertain or changed controls to SMEs.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Large questionnaires repeat similar questions, answers drift across deals, and scarce security experts spend time finding the same policy and control evidence.
Security SMEs, sales engineers, legal, privacy and deal-desk teams
Trigger to act: Enterprise deals are delayed, questionnaire volume is rising, trust-center content is inconsistent, or the company is entering regulated segments.
The result you can model before you sign.
Illustrative only: 40 questionnaires/month × 12 SME hours removed × $95 loaded hourly cost = $45,600 monthly capacity. Revenue acceleration is deal-specific and should be tracked separately.
The outcome, plainly: Draft cited, confidence-scored questionnaire responses from approved evidence and route only uncertain or changed controls to SMEs.
Inputs in. A cited, review-ready result out. Your expert decides.
A Permission-aware RAG copilot. Every material fact is grounded in an allowed source and returned with its identifier, no invented data.
Claude Sonnet 4.6 or GPT-5.6 Terra for complex grounded work, select by task-level evaluation; Gemini 2.5 Flash, GPT-5.4 mini or Claude Haiku 4.5 for high-volume routing and drafting. PostgreSQL + pgvector or managed vector store; policy rules and evaluator service.
- Questionnaire
- Question taxonomy
- Policies
- SOC/ISO reports
- Architecture/security docs
- Prior approved answers
AI-Native, not autonomous. Judgment stays with your people.
The machine does the work; the human’s role narrows to the one thing that matters, judgment. That constraint is what makes it safe to deploy.
Security/legal/privacy owners approve every new, low-confidence, customer-specific, contractual, or forward-looking statement.
A scorecard, not a demo. We baseline what breaks in production.
Every deployment ships with an evaluation suite. These are the numbers we baseline before launch and monitor after.
The category is crowded. Most of it isn’t built for your workflow.
Fixed-scope, tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in from day one. A price you own, not a subscription you rent.
It plugs into the stack you already run.
No rip-and-replace. Access is scoped to the minimum data necessary, isolated per tenant, and fully logged.
Transparent by design. The build price buys the workflow and the proof.
A fixed implementation fee plus a monthly bill that scales with volume and governance. No hidden seats.
- ✓ One process / scope
- ✓ Live workflow on your data
- ✓ Baseline evaluation suite
- ✓ Measured vs. current process
- ✓ Full scope & integration
- ✓ Human-review UI & audit trail
- ✓ Write-back to your systems
- ✓ Production evals & monitoring
- ✓ Multi-facility rollout
- ✓ Advanced security & compliance
- ✓ Custom control & escalation
- ✓ Dedicated evaluation program
10,000 to 35,000 grounded questions per month plus indexing and vector search.
Planning assumptions, not vendor quotations. Your approved policy repository and other platform licenses are separate and owned by you. Figures confirmed during scoping.
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
Questions serious buyers ask.
Does the AI act on its own?
No. Security/legal/privacy owners approve every new, low-confidence, customer-specific, contractual, or forward-looking statement. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: No invented certification, control, roadmap commitment, or breach statement; no customer response without named owner approval; no access beyond source ACLs..
How do you stop it inventing facts?
Every material claim is grounded in an allowed source record and returned with its source identifier. The system separates observed facts, model inference, and missing information, and routes to a human whenever confidence is low, evidence conflicts, or an adverse outcome is possible.
What does it cost to run each month?
A usage bill of roughly $500 to $3,800 per month (10,000 to 35,000 grounded questions per month plus indexing and vector search), plus a $2,600 per month managed retainer for evaluation, monitoring and maintenance. Your existing platform licenses are separate and already yours. Exact figures are confirmed during scoping.
Do we need a ChatGPT or Claude subscription?
No consumer ChatGPT or Claude subscription is required for the production workflow. The client needs an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.
How is this different from Conveyor?
Tools like Conveyor, Loopio, Responsive are broad platforms you adapt to. This is a fixed-scope implementation tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in, and a transparent price instead of a seat subscription.
How long until it is live, and how do we prove it works?
We baseline the response time first, then measure against that baseline. You see the scorecard before expanding scope: the evaluation suite ships with the system, not as an afterthought.
Bring your real numbers. Leave with a fixed-scope plan.
A 30-minute engineering-led working session, no slideware. You leave with a sized opportunity estimate, a fixed-scope pilot plan, and the integration & human-review path mapped.
VP of Growth at ViitorCloud · senior delivery owner confirmed before paid work