Reguloft

AI-powered regulatory change management platform for life sciences that automates document processing, configurable clinical and operational workflows, and compliant content review and deployment with strong governance and traceability.

The Problem

“Regulatory change management in life sciences is slowed by document-heavy, compliance-critical workflows”

Organizations face these key challenges:

1

High volume of regulatory and clinical documentation

2

Repetitive administrative work for regulatory and operations teams

3

Risk of inaccurate AI outputs without guardrails and source grounding

4

Strict data security and privacy requirements for regulated content

Impact When Solved

Reduce time spent reviewing and summarizing regulatory documentsAccelerate clinical and operational workflow execution with configurable automationShorten MLR review and content deployment cyclesImprove consistency of compliance checks and approval routing

The Shift

Before AI~85% Manual

Human Does

  • •Read regulatory updates and clinical documents, then summarize required changes
  • •Route SOPs, submissions, promotional content, and operational tasks through manual approval steps
  • •Compare document versions, track comments, and maintain status in spreadsheets or checklists
  • •Coordinate MLR reviews, resolve feedback, and confirm final approvals before deployment

Automation

  • •No meaningful AI support in the legacy process
  • •Limited automation for storing documents and sending basic notifications
  • •Minimal system assistance for workflow tracking across disconnected tools
With AI~75% Automated

Human Does

  • •Approve regulatory interpretations, content changes, and final workflow decisions
  • •Review flagged exceptions, low-confidence outputs, and policy-sensitive cases
  • •Provide MLR judgment on claims, risk, and compliance before release

AI Handles

  • •Ingest, classify, summarize, and compare regulatory, clinical, and promotional documents
  • •Extract key fields, draft change logs, review notes, and other administrative outputs
  • •Orchestrate configurable workflow routing, task assignment, escalations, and SLA monitoring
  • •Pre-check content against approved policies and references, then prepare grounded review packages

Operating Intelligence

How it works

Humans set constraints. AI generates options.

Humans choose what moves forward.

Selections improve future generation quality.

Confidence84%
ArchetypeGenerate & Evaluate
Shape6-step branching
Human gates2
Autonomy
50%AI controls 3 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapebranching

Step 1

Define Constraints

Step 2

Generate

Step 3

Evaluate

Step 4

Select & Refine

Step 5

Deliver

Step 6

Feedback

AI lead

Autonomous execution

2AI
3AI
5AI
gate
gate

Human lead

Approval, override, feedback

1Human
4Human
6↺ Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

Humans define the constraints. AI generates and evaluates options. Humans select what ships. Outcomes train the next generation cycle.

The Loop

6 steps

1 operating angles mapped

Operational Depth

Technologies

Technologies commonly used in Reguloft implementations:

Critical thinking and cross-checkingOther
4 mentions
Guiding principles for safe useOther
4 mentions
Large Language ModelsLLM/Model
4 mentions
Safe data input practicesOther
3 mentions
Veeva CTMSOther
2 mentions

Key Players

Companies actively working on Reguloft solutions:

Microsoft CopilotGoogle Gemini for WorkspaceOpenAI enterprise assistants

Real-World Use Cases

AI-assisted pharmaceutical content ecosystem for creation, MLR review, and deployment

Bristol Myers Squibb is using AI to help make marketing and medical content faster, check it during review, and get it out to the right places while still following pharma rules.

Document generation and review augmentation across regulated workflow stepsearly production / active exploration within an enterprise content workflow
10.0

Agentic AI for workflow automation in life sciences operations

AI agents can take on parts of repetitive office work, helping teams complete regulated tasks faster and freeing people for harder decisions.

multi-step workflow orchestration and decision supportemerging but actively productized; iqvia presents agentic ai as a current offering and references custom-built ai agents with nvidia.
10.0

Large language model workflow for regulatory document processing and administrative automation

EMA is guiding staff to use text-generating AI tools to read long documents, mine information, and handle routine office work more safely.

Generative text assistance for summarization, extraction, and drafting supportgoverned operational use with formal guidance, not a single standalone product
10.0

Replacing rigid manual trial workflows with configurable clinical operations software

Swap hard-to-maintain spreadsheets and rigid legacy systems for software that can adapt to complex trial workflows.

Process digitization and configurable workflow managementmature modernization initiative; framed as a necessary upgrade for scaling in-house clinical operations.
10.0

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