Healthcare

Life Sciences & Research

Protocol, Trial & Regulatory Document Operations

Research runs on documents that must be exact: protocols, consent forms, study reports, submissions and the correspondence that accompanies them. The work of keeping them consistent with each other, and with the regulation that governs them, is slow and unforgiving. Scalata's agentic AI platform reads across the whole document estate and shows where it disagrees with itself.

Cross-documentConsistency checking across the study estate
AutomatedProtocol, report & submission drafting support
TraceableEvery claim back to its source data
ControlledVersioning and approval on every artefact

How it works

The four-step journey

The same shape every time: name what is going wrong, put the documents somewhere they can be read, let people ask questions of them, and then hand the repeating parts to agents that do not need asking.

  1. 01

    Confronting Document Volume & Version Drift

    A study generates protocols, amendments, consent forms, reports and submissions, each version of which must agree with the others. Reconciling them is manual, and drift is usually found late — during a submission or an inspection.

    High document volumeVersion driftManual consistency checkingLate-stage inspection findings
  2. 02

    Building a Unified Research Document Core

    The study estate is ingested with its version history intact, so every artefact is readable alongside the ones it depends on rather than as an isolated file.

    Document AIProtocol & amendment parsingConsent & report ingestionVersion history capture
  3. 03

    Activating Intelligent Consistency & Evidence Analytics

    Claims in a report can be traced to the data that supports them, and inconsistencies between a protocol, its amendments and the documents derived from them are surfaced as they appear.

    Conversational AIClaim-to-source traceabilityCross-document consistencyRegulatory requirement mapping
  4. 04

    Full Automation with Proactive Research AI Agents

    Drafts are assembled from the approved source material, inconsistencies are raised while they are cheap to fix, and agents keep the submission checklist current as the estate changes.

    Draft assembly from sourceInconsistency alertsSubmission checklist trackingInspection readinessAI Agents

Strategic Outcome

Documents stop disagreeing with each other quietly. Inconsistencies surface while a study is running rather than during a submission, and every claim can be shown back to the data underneath it — which is the difference between being ready for an inspection and preparing for one.

Who Scalata serves

  • Medical writers assembling study reports and submissions
  • Regulatory affairs teams tracking submission requirements
  • Clinical operations teams managing protocol amendments
  • Quality teams preparing for audit and inspection
  • Study managers watching document status across sites
  • Data managers linking claims to underlying evidence

What you can generate

  • Cross-document consistency and drift reports
  • Claim-to-source traceability matrices
  • Draft study documents assembled from approved sources
  • Submission checklists with current status
  • Inspection readiness summaries

Turn weeks of expert work into minutes

See how Scalata fits your team, your data, and your controls.

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