Stop Investigating False Positives. Start Confirming Real Issues.

CluePoints Intelligent Query Detection (IQD) applies agentic artificial intelligence (AI) to the most resource-intensive part of clinical Data Management (DM): complex, judgment-based manual listing review. With 80% or greater precision and greater than 99% recall, validated across 100 or more production studies, IQD shifts DM work from investigation to confirmation. Every finding comes with supporting evidence. One click submits it directly to Veeva EDC. Your team stays in control.

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Precision AI for Manual Listing Review,  with Full DM Team Control

CluePoints IQD is not a broad data quality platform. It is a depth-first intelligence layer focused exclusively on complex, judgment-based manual listing review: the 60–70% of DM reconciliation effort that consumes the most skilled capacity and introduces the most late-stage timeline risk. Agentic AI investigates. Your team confirms and acts.

Agentic AI Discrepancy Detection

Automated agentic AI performs the investigation phase of manual listing review, identifying true cross-domain discrepancies with 80% or greater precision and 99% or greater recall across complex, judgment-based checks. Validated across 100 or more production studies, including co-development with GSK.

Evidence-Backed Findings

Every detected discrepancy is surfaced with the supporting evidence that informed the finding, so data managers review the complete case, confirm with confidence, and take action without conducting the investigation themselves.

One-Click Query Submission to Veeva EDC

Auto-generated, editable query text is submitted directly to Veeva EDC in a single action, eliminating manual transcription, reducing the time from discrepancy identified to query posted, and maintaining a complete audit trail throughout.

High-Precision Accuracy

80% or greater precision means the discrepancies reaching your team are real, not false positives that consume investigation time. Greater than 99% recall means nothing material is missed. Manual listing review precision typically runs around 40%. IQD doubles it.

Adaptive Learning Model

IQD continuously refines through user interaction, maintaining and improving detection accuracy as studies evolve, protocols change, new sites are added, and data patterns shift throughout the study lifecycle. No custom programming required when expanding to new trials.

Full Traceability & Audit Trail

Every signal, evidence set, confirmation decision, and query action is logged in a complete, regulatory-ready audit trail from detection through resolution, consistent with 21 CFR Part 11 requirements.

How CluePoints IQD Solves Your  Biggest Listing Review Challenges

From Investigation to Confirmation:  A Fundamental Shift

Traditional manual listing review forces DM teams to spend the majority of their time on investigation: reviewing long data listings, identifying potential discrepancies, cross-referencing across data domains, and deciding whether what they found is real. Most of what they investigate turns out to be noise. Manual precision typically runs around 40%. IQD automates the investigation phase so data managers focus on confirmation and action. Faster. Cleaner. More predictable. By reducing time spent manually reviewing data, teams can focus on higher-priority tasks, accelerate issue resolution, and improve regulatory compliance.

Your Team Confirms Real Issues. It Does Not Chase Noise.

Advanced large language models (LLMs) in IQD accurately detect data discrepancies, significantly minimizing false positives and reducing the burden of unnecessary investigations. With 80% or greater precision, cleaner data across sites, and less manual effort, teams maintain trial integrity and ensure higher-quality regulatory submissions.

Faster Queries, Fewer Rejections, Shorter Cycles

Automated query detection enables users to raise queries with just a few clicks, reducing resource strain and improving efficiency. IQD compresses the time from discrepancy identification to query submission by auto-generating editable, evidence-backed query text. Queries submitted through IQD are specific, clearly articulated, and grounded in supporting evidence, so site rejection and clarification rates decline, back-and-forth exchanges shorten, and first-pass acceptance rates improve. DM teams recover capacity to focus on higher-value tasks.

Standardized Queries That Sites Actually Respond To

IQD suggests standardized query text for each confirmed discrepancy, reducing redundancy and ensuring clear, consistent communication with sites. This minimizes miscommunication and back-and-forth exchanges, enables faster query resolution, and strengthens site relationships by making queries specific rather than generic.

No More Manual Programming to Maintain Listings

IQD eliminates manual programming by leveraging AI-driven models that continuously improve at detecting and highlighting data discrepancies. Automating query listings frees data managers to focus on data quality oversight rather than manually maintaining and updating listings. The model adapts as study protocols evolve and new data patterns emerge, with no custom programming required when expanding across trials.

VALIDATED AGENTIC AI WITH HUMAN CONTROL

Your Team Confirms. IQD Investigates.  Regulators Can Follow Every Step.

CluePoints IQD is designed for DM teams that want the productivity benefits of AI without giving up control over decisions or the ability to demonstrate those decisions to regulators. Every finding reaches your team with supporting evidence before any action is taken. Confirmation is yours. The query is yours. IQD performs the investigation that currently consumes most of your team's listing review time. The complete audit trail, from discrepancy detection through query resolution, is captured automatically in a 21 CFR Part 11-compliant environment and is available for inspection at any time.

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