Conveyor Automates Security Reviews and RFPs: Toward the End of B2B Paperwork?

Sales teams lose weeks answering vendor security questionnaires and RFPs. Conveyor’s $20 million Series B funds an AI agent that claims to complete 90 % of this work autonomously. Faster cycles, leaner pre-sales teams, and higher conversion are attractive—but not risk-free. ▶
This article analyses business impact, no-code synergies, concrete use cases, governance issues, and a pragmatic six-month roadmap.

1. From Paperwork to Pipelines: Business Implications of AI-Driven Security Reviews

Metric	Typical baseline	With AI agent (Conveyor estimate)
Time to complete 150-question security review	20–30 hours	2–3 hours (human validation only)
Sales cycle length (mid-market SaaS)	90–120 days	60–90 days
Pre-sales engineer allocation	1 FTE per 8 deals	1 FTE per 20+ deals
Renewal churn caused by delayed audits	4–6 %	95 % only auto-approved.
Model drift as policies change	Weekly sync from GRC system; scheduled re-embedding.
Compliance with AI governance frameworks	Map agent behaviour to ISO/IEC 42001 controls.
Cost overruns (token usage & licensing)	Track per-deal AI cost; benchmark vs. saved billable hours for pre-sales.

5. Six-Month Roadmap to 80/20 Automation

1. Audit current process
   • List questionnaires handled per quarter, average response time, error rate.
2. Select AI engine
   • Compare Conveyor SaaS vs. API-first alternatives; evaluate on security posture and TCO.
3. Orchestrate with no-code
   • Prototype intake → AI → review → delivery workflow in Airtable + Zapier; add Slack approvals.
4. Pilot on low-risk deals
   • Target renewals before new logo sales; measure accuracy and cycle reduction.
5. Scale & optimise
   • Automate evidence refresh; integrate with CRM to trigger agent at proposal stage.
6. Govern
   • Establish review SLAs; maintain an audit trail for each generated answer.

Target: Reach 80 % automated coverage and breakeven on deployment costs within six months.

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Key Takeaways

• AI agents can compress security questionnaire effort by up to 90 %, directly shortening B2B sales cycles.
• No-code tools (Zapier, Make, Airtable) act as orchestration fabric, turning isolated AI outputs into repeatable compliance pipelines.
• Benefits are most pronounced in SaaS, fintech, and health-tech where due-diligence drag is acute.
• Data isolation, human review, and policy refresh loops are mandatory to avoid compliance and reputational risks.
• A staged rollout—audit, pilot, scale—achieves the 80/20 automation threshold within roughly six months.