Move from AI experimentation to measurable business value
Life sciences organizations have no shortage of information. The challenge is finding the right content, understanding its context, and using it efficiently—without compromising quality, security, or control.
Court Square Group helps pharmaceutical, biotech, medical device, and contract research organizations apply generative AI to high-value workflows. Our solutions connect approved content and data across your organization, retrieve the most relevant information, and generate source-grounded first drafts for expert review.
The result: less manual searching, copying, rewriting, and reconciliation. Your teams can work faster while maintaining the human oversight, traceability, and governance required in a regulated environment.
Generative AI That Works with Your Content, Systems, and Processes
Public AI tools can generate text. Life sciences organizations need more.
Court Square Group designs AI workflows around your approved content, business rules, templates, systems, and review processes. Rather than relying on an ungrounded response from a general-purpose model, the solution retrieves relevant information from authorized sources and uses it to support a specific task.
Depending on your requirements, the solution can connect with cloud or on-premises repositories, enterprise applications, document management systems, and customer-approved private or public large language models. It can help your teams:
- Find relevant information across disconnected repositories
- Extract and structure content from complex documents
- Compare new requests with previously approved work
- Generate source-grounded first drafts using approved templates
- Translate content using controlled terminology and review gates
- Route drafts for human review, editing, approval, and release
- Preserve versions, metadata, source references, and audit history
- Capture reviewer corrections to improve future outputs
Where Generative AI Can Create Value
Accelerate clinical trial start-up documentation
Preparing informed consent forms, monitoring plans, study plans, and country- or site-specific documents often requires teams to locate information in protocols, investigator brochures, prior studies, and CRO files—and then rewrite it for each use.Generative AI can retrieve relevant approved content and help create initial drafts based on current study requirements, prior precedent, regional requirements, and established terminology. Human reviewers remain responsible for checking, editing, and approving every document. Faster document preparation and fewer reconciliation cycles can help reduce delays in site activation and First Patient In.
Streamline regulatory document preparation
Reduce repetitive work associated with regulatory forms, cover pages, content variations, and submission documents. AI-assisted extraction and generation can prepopulate templates, support content reuse, and produce first drafts for regulatory review. Translation workflows can also help teams prepare multilingual content while preserving approved terminology and required review steps.
Improve RFI and RFP response development
Search historical questions, responses, supporting documents, and outcomes using meaning—not just keywords. The solution can identify relevant prior answers and generate a contextual first draft for review. Teams gain a faster path from a new request to a consistent, evidence-based response while maintaining version history and traceability.
Turn organizational knowledge into usable answers
Valuable knowledge often sits across document libraries, operational systems, email archives, and departmental repositories. Semantic search and retrieval-augmented generation can connect users with the most relevant information and synthesize it into a useful response. This can support audit preparation, quality inquiries, customer questions, operational reporting, and internal decision-making.
Automate repeatable content workflows
Configure multi-step workflows for extraction, classification, summarization, drafting, translation, comparison, and approval. Each workflow can reflect the organization’s content types, terminology, permissions, and operating procedures—allowing teams to scale content-intensive work without losing control.
Designed for Human Oversight and Traceability
In regulated work, speed is useful only when the output can be reviewed, understood, and governed.
Court Square Group builds human-in-the-loop controls into the workflow. Subject-matter experts can review source references, edit generated content, document decisions, and approve the final output. Depending on the application and system configuration, records can be maintained with role-based access, version control, audit trails, electronic signatures, and controlled publishing.
This approach helps organizations use generative AI as an assistive tool—not an unchecked decision-maker.
A Practical Path from Pilot to Production
Successful generative AI projects begin with a well-defined business problem, reliable source content, and measurable success criteria. Court Square Group uses a phased approach to reduce risk and focus investment where it can create the most value.
1. Identify and prioritize the use case
We work with business, technical, quality, and compliance stakeholders to define the workflow, users, source content, pain points, risks, and expected business outcomes.
2. Assess content and systems
We evaluate source repositories, document quality, metadata, integrations, permissions, templates, and governance requirements. This establishes whether the content is ready to support dependable retrieval and generation.
3. Configure and test a focused pilot
We build a controlled workflow around a representative dataset. Outputs are reviewed against agreed criteria such as accuracy, relevance, time saved, consistency, traceability, and user acceptance.
4. Refine with expert feedback
Reviewer edits and feedback reveal where prompts, source content, metadata, templates, or process rules should be improved. These lessons inform the production design.
5. Validate, deploy, and scale
After the solution meets the agreed requirements, we support deployment, documentation, training, change management, and ongoing improvement. The same foundation can then be extended to additional content types and workflows.
Why Court Square Group?
Generative AI requires more than a model. It requires a clear use case, dependable information, sound architecture, controlled workflows, and people who understand how life sciences teams operate.
Court Square Group brings together:
- Decades of experience supporting regulated life sciences organizations
- Expertise in clinical, regulatory, quality, and business workflows
- AI-enabled search, extraction, classification, and content generation
- Integration across cloud, on-premises, and enterprise systems
- Secure, audit-ready content management through RegDocs365 and the ARCC
- Qualification, validation, compliance, and change-management services
- A vendor-neutral approach that can support customer-approved AI models and technology environments
We focus on building an AI solution that fits the work—not forcing the work to fit the technology.
Put Generative AI to Work on a High-Value Process
Start with one workflow where manual searching, rewriting, or document preparation is consuming time and slowing the business. Court Square Group can help you assess the opportunity, select the right use case, and build a focused pilot with clear measures of success.