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Nabla-X TrialSentinel

Catches what a six-month review cycle misses.

Data Reliability's anomaly detection applied to clinical trial and research data — the one Nabla-X vertical without a dedicated product yet. Checks new records against patterns across sites, forms, and systems in real time, instead of waiting for a periodic manual review to catch a problem.

Illustrative alert — target output, based on Data Reliability's real engine
AlertSite 7 adverse-event reporting rate 40% below the trial's other 11 sites
PatternReporting gap concentrated in Week 3-4 forms, not present in Week 1-2
Cross-ReferenceNo corresponding drop in enrollment or visit completion at Site 7
Suggested ActionFlag for data monitoring committee review before the next scheduled interim analysis

Core Capabilities

Real-Time, Not Periodic

Checks new trial records against cross-site patterns continuously, instead of waiting for a scheduled review cycle.

Cross-Site, Cross-Form Comparison

Compares patterns across sites, forms, and systems to catch anomalies a single-site view would miss.

The One Vertical Without Coverage

Fills the one Nabla-X vertical — clinical trials and research — with no dedicated product yet.

How TrialSentinel Would Work

Planned design — this pipeline does not exist yet.

1. Extend Data Reliability to Trial Data Schemas

Points the existing anomaly engine at trial-specific structures — adverse event forms, enrollment records, site data.

2. Compare Across Sites and Forms

Checks new records against patterns observed across other sites and form types, not just historical trend for one site.

3. Flag for Committee Review

Surfaces anomalies to a data monitoring committee in real time, rather than waiting for the next scheduled interim analysis.

Multiple Sites, One Continuous Timeline

Conceptual pipeline — every site feeds the same continuous check, instead of its own periodic review.

Site ASite BSite CSite DContinuous timeline — every record checked as it arrivesTrialSentinel EngineSchema Extension · Pattern Matching · Scoring(extends Data Reliability — real)Cross-Site ComparisonCommittee Alert

How TrialSentinel Would Think

The reasoning approach this concept is designed around.

Zooming into one moment on the continuous timeline

Conceptual — illustrates the intended per-record evaluation. No part of this pipeline is built.

Record arrivesCompared to peer sitesAnomaly scoredFlagged in real time

Real-Time Over Periodic

The core bet is that continuous checking catches what a six-month review cycle structurally cannot — not a new detection method, a different cadence.

  • •Same anomaly logic as Data Reliability, different cadence
  • •Designed to run per new record, not per review cycle

Cross-Site Is the Signal

A single site's numbers alone are often unremarkable — the anomaly shows up in comparison to other sites running the same trial.

  • •Baseline is peer sites, not just historical self

Fills a Named Gap

Explicitly positioned as the one Nabla-X vertical without a dedicated product — not a speculative new market.

  • •Directly extends existing positioning, not a new vertical bet

Extends a Real Engine

Like FraudSentinel, this reuses Data Reliability's working anomaly detection rather than building new detection logic from scratch.

  • •Lower build risk than concepts with no real parent
Concept Architecture

Planned Architecture

Nothing below is built. This describes the intended design and its dependencies.

Dependency: TrialSentinel applies Data Reliability's anomaly detection engine (real) to clinical trial and research data specifically — one of the more direct reuses of an existing engine on this roadmap, alongside FraudSentinel and UptimeSentinel.

Review cadence — why continuous beats periodic

Conceptual comparison — illustrates the intended cadence, not measured trial data.

Traditional review cycleCheckpoint roughly every 6 monthsAnomaly occurs —undetected until next reviewTrialSentinel — continuous (concept)Checks run as each record arrivesSame anomaly —caught almost immediately
Schema ExtensionNot yet designed
Cross-Site Pattern MatchingUnspecified
Anomaly ScoringUnspecified
Extends Data Reliability (real)Not started
Full buildBlocked on dependency
⏱️

Continuous, Not Periodic

Checks run as records arrive, not on a six-month cycle.

🔀

Cross-Site Comparison

Baseline is peer sites in the same trial, not just one site's history.

✅

Real Parent Engine

Extends Data Reliability's working anomaly detection, not a new engine.

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