Compress CAPA cycle time, lift complaint-to-CAPA signal quality, and cut the volume of trend-related 483 exposure. AI-assisted intake, root-cause investigation, and effectiveness verification — deployed inside your existing QMS.
CAPA is the single most-cited area in FDA Form 483 observations (~12.4% of all findings) and appears in more than 60% of medical device Warning Letters. It is also the first metric a quality diligence lead pulls in an acquisition. Alterra AI's CAPA + Complaint deployment targets the two failure modes that drive both problems: slow investigations and weak signal detection.
The regulation (21 CFR 820.100 for CAPA, 820.198 for complaints — now anchored under QMSR + ISO 13485:2016) is clear. The failure modes are operational:
Reads intake, classifies severity, flags MDR-reportability against 21 CFR 803, and drafts the initial investigation record inside your QMS. Human reviewer confirms and signs.
Pulls related complaints, service records, nonconformances, and DHR data. Proposes candidate root causes with linked evidence. Reviewer approves or rejects — every action is logged.
Monthly signal report across complaints, nonconformances, and returns. Flags emerging clusters before they meet CAPA thresholds. Feeds Management Review with pre-built visuals.
Auto-schedules effectiveness checks, monitors related complaint volume post-closure, and raises a re-open flag if the trend re-emerges. Reviewer decides.
| Metric | Before (typical) | After (target) | Source of estimate |
|---|---|---|---|
| Median CAPA cycle time | 140–180 days | < 90 days | Public benchmarks + Alterra project modeling |
| Investigation drafting effort | 12–20 hrs per CAPA | 3–6 hrs per CAPA | Alterra AI project estimate |
| Complaint-to-CAPA conversion | Ad hoc | Signal-driven, monthly | Alterra AI project estimate |
| MDR-reportability triage lag | 3–7 days | < 24 hours | Alterra AI project estimate |
| Effectiveness re-open rate | 5–15% | < 5% (verified) | Alterra AI project estimate |
Ranges based on public FDA 483 trend data (FDA Group, MedDeviceGuide 2026), FDA warning-letter analyses, and Alterra AI internal project modeling. Individual results vary with baseline CAPA maturity and complaint volume.
What a diligence team will pull: a CAPA aging report, complaint-to-CAPA conversion rate, and repeat-finding rate. All three improve within one quarter of deployment — enough for a QBR narrative or a QoR data room addendum. This is the fastest-moving KPI on the medtech quality dashboard.
Every AI action is a controlled process step with a logged reviewer, versioned record, and traceability to source data. Aligns to 21 CFR 820.100 (CAPA), 21 CFR 820.198 (complaints), ISO 13485:2016 clauses 8.2.2, 8.3, 8.5.2, and MDR reportability under 21 CFR 803. EU MDR PMS and vigilance evidence is generated as a side effect, not a parallel workflow.
Class II SMB with growing complaint volume, CAPA aging over 100 days, at least one recent trend-related 483 or internal audit finding, or a leadership team that wants a defensible CAPA metric to show at the next board meeting.
Pre-launch companies with no complaint stream (nothing to trend yet), or companies currently under an active Warning Letter for CAPA — those need remediation-first consulting before automation.
48-hour read-only review of your CAPA and complaint queues. Cycle-time and conversion baseline. Prioritized punch list ranked by risk.
Book the 48-hour Assessment