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Prototype · Option A John A. — control owner
Option A · PM Analysis

Auto-Collected with Exception Review

Integrations pull evidence on a schedule. Owner only sees the gaps.
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Thesis

The biggest GRC pain is manual evidence collection — control owners spend 30%+ of audit prep time hunting screenshots, exports, and sign-offs that already exist in source systems. If we automate the pull and leave only the exceptions for human review, we eliminate the highest-volume, lowest-judgment work in the entire compliance lifecycle.

Target user

👤
Control owner
IT / Security / Ops
Frequency
Daily during audit prep, weekly otherwise
Tools today
Email + spreadsheets + screenshots + Slack
Core pain
Spends 30%+ of audit prep manually re-collecting evidence that lives in connected systems. The repetitive nature breeds errors and burnout.
Win state
Logs in once a day, sees a tight queue of 5–10 exceptions to handle. Everything else is already gathered, mapped, and stamped.

Business Model Canvas

The nine standard blocks, mapped to this option.

Customer Segments
SOC 2 / ISO 27001-compliant SaaS, 50–2,000 employees · expanding into FinServ + Healthcare with HIPAA / HITRUST / NIST CSF needs
Value Proposition
"Cut audit prep time 60–80% by automating evidence pulls from systems you already use."
Channels
AuditBoard direct sales · co-sell with audit firms (Big 4 + mid-market) · partner referrals
Customer Relationships
High-touch implementation (6–8 weeks) · annual renewal · CSM check-ins quarterly
Revenue Streams
Subscription per-integration ($10k–$30k/yr base + per-connector upsell) · enterprise tiering by control count
Key Resources
Integration engineering team · control-mapping ontology IP · SOC 2 Type II as the platform itself
Key Activities
Maintain integrations against API drift · ship 1–2 new connectors per quarter · keep the control library current
Key Partners
API providers (AWS, Okta, GitHub, ServiceNow, Snowflake) · Big 4 + mid-market audit firms · SI partners
Cost Structure
Integration engineering (high) · cloud infra (med) · platform compliance (med) · sales (high)

Pros

  • Highest volume of work eliminated immediately — 10s to 100s of hours saved per audit cycle.
  • Defensible moat: integration breadth × control-mapping ontology. Hard to copy at scale.
  • Crystal-clear ROI — hours saved is directly quantifiable in the first cycle.
  • Aligns with AuditBoard's existing direct sales motion and current customer expectations.
  • Existing customers can adopt with minimal workflow disruption.

Cons / risks

  • Integration coverage is the bottleneck — each new connector is months of engineering.
  • API drift is constant operational cost (vendors break their APIs).
  • Some critical evidence has no integration (paper sign-offs, screenshots of physical security).
  • Doesn't answer "what evidence do I need?" — assumes the control library is already mapped.
  • Less compelling for small teams with few integrated systems.

Build & time

Build complexity
High
Time to MVP
6–9 months
Time to "wow"
~3 months

Path to GA

  1. Build 3 priority integrations (AWS IAM, Okta, GitHub PRs).
  2. Map them to the top 50 SOC 2 controls.
  3. Pilot with 5 design-partner customers to validate auto-mapping accuracy.
  4. Expand library to 200 controls + add Jira / ServiceNow / Snowflake.
  5. Open self-serve connector marketplace (long-tail integrations).

Fit assessment

★★★★★
Strong fit for AuditBoard. Builds on their existing strengths (control library, framework crosswalks) and is the most defensible long-term — not a wrapper, real IP. The path AuditBoard would naturally take.