Cloudbyz eClinical, built natively on Salesforce Agentforce, adds a new AI agent that reads your protocol, watches your operational data, and surfaces compliance risk before it becomes a deviation.
Every clinical trial begins with a protocol that defines, in painstaking detail, exactly when a patient should be seen, what should be assessed, and within what window each visit must occur. And yet, within weeks of first-patient-in, that document is effectively frozen in a PDF or eTMF folder while the trial itself moves — sites onboard on a rolling basis, monitors rotate, visit schedules slip, and deviations accumulate long before anyone has the full picture.
By the time a Clinical Research Associate (CRA) or Clinical Operations Manager notices that a particular visit is generating the same deviation at site after site, the pattern has often already repeated itself a dozen times. By the time a monitoring visit report calls out an out-of-window visit, the visit has already happened. Compliance, in most trials today, is reactive by design: teams look backward at what went wrong rather than forward at what is about to.
This is the gap the Protocol Intelligence Agent is built to close.
The Protocol Intelligence Agent is a new AI agent on Cloudbyz eClinical, built on Salesforce Agentforce, that reads and understands the schedule of assessments directly from the protocol and continuously analyzes operational data against it. Instead of waiting for a query, a report request, or a monitoring visit to trigger a review, the agent works proactively — scanning visit dates, deviation logs, and site-level patterns to surface compliance risk while there is still time to act on it.
It is important to be clear about what this agent does and does not do. The Protocol Intelligence Agent generates insights and alerts only. It never edits, creates, or resolves deviation records. Every finding it produces is a prompt for a human decision-maker — a Clinical Director, a Clinical Operations Manager, a CRA, or a Clinical Data Manager — to review, investigate, and act on. The agent's role is to make sure the right risk reaches the right person early, not to replace clinical judgment or documentation workflows.
The Protocol Intelligence Agent is designed around four roles that each interact with protocol compliance differently, but that all currently rely on manual review, static reports, or institutional memory to catch risk early:
Instead of digging through the protocol document, the schedule of assessments, and amendment history separately, users can ask the Protocol Intelligence Agent direct questions — "What is the visit window for Week 12?" or "What assessments are required at the unscheduled visit?" — and receive answers grounded in exact source citations back to the protocol text. This closes one of the most persistent gaps in trial execution: the distance between what the protocol says and what site staff and monitors actually remember or interpret in the moment.
The agent continuously analyzes deviation data across sites, visits, and deviation categories to detect systemic trends — for example, identifying that a single visit is generating a disproportionate share of the same deviation type across multiple sites. This shifts deviation review from a per-incident activity to a pattern-recognition exercise, surfacing structural protocol or site-training issues that would otherwise only become visible after a large enough sample of individual deviations had already occurred.
When a risk has already emerged at one site, the Protocol Intelligence Agent can warn newer or later-activated sites before they reach the same visit, using patterns already observed elsewhere in the study. This turns institutional knowledge that would normally live in a monitor's head — or not be discovered at all — into a systematic, study-wide safeguard.
The agent checks actual visit dates against the protocol-defined visit windows and flags visits that are trending out of window before they become formal deviations. This is one of the clearest examples of moving compliance upstream: rather than documenting a deviation after the fact, the agent gives site staff and CRAs a window to intervene while the visit can still be scheduled correctly.
Ahead of a monitoring visit, the agent builds a site risk briefing, automatically ranked by severity, with patient safety findings surfaced first. CRAs walk into the visit with a prioritized agenda grounded in current operational data rather than having to reconstruct the risk picture manually from multiple systems.
Under the hood, the agent combines two distinct capabilities: structured rules for detection — checking dates against windows, tallying deviation patterns, comparing site performance — and grounded document retrieval for explanation, tying every finding back to the specific protocol language that defines it. The result is that every alert is both computed from real operational data and explainable in the protocol's own words, rather than being a black-box output.
Compliance moves upstream. Deviations are where trials quietly lose time, budget, and credibility — through corrective action plans, root cause analyses, and sponsor and auditor scrutiny. Catching an at-risk visit or an emerging site pattern before it becomes a formal deviation changes the entire cost structure of compliance management.
Patient safety comes first, systematically. By prioritizing safety findings in every briefing and surfacing timing problems before they compound, the agent ensures that the most consequential risks are never buried in a backlog of lower-priority items.
Audit readiness improves by design. The agent systematically confirms that deviations are being documented consistently, closing the gap between what happened operationally and what is captured in the trial master file — a gap that regulatory inspectors and sponsor auditors are quick to find.
The protocol becomes a living operational tool. Rather than a reference document consulted at study start-up and then largely forgotten, the schedule of assessments becomes the ongoing standard against which every site, every visit, and every deviation is continuously measured — for the life of the study.
As part of the Cloudbyz eClinical and AI platform, the Protocol Intelligence Agent inherits the same native Salesforce architecture, data model, and security framework as the rest of Cloudbyz's clinical operations, pharmacovigilance, regulatory affairs, and validation products. That means protocol intelligence isn't a bolt-on analytics tool sitting outside the system of record — it operates directly against live CTMS, eTMF, and deviation data already in Cloudbyz eClinical, with no duplicate data entry and no separate reconciliation step.
Clinical trial teams have never lacked protocols, deviation logs, or visit schedules — what they have lacked is a systematic way to connect the three in real time, at scale, across every site in a study. The Protocol Intelligence Agent gives Clinical Directors, Clinical Operations Managers, CRAs, and Clinical Data Managers exactly that: a proactive, explainable, protocol-grounded layer of intelligence that catches risk while there's still time to do something about it — without ever taking the decision, or the documentation, out of human hands.
To see the Protocol Intelligence Agent in action on Cloudbyz eClinical, reach out to the Cloudbyz team for a demo.