AI document creation for a consulting firm

Objectives

1. Automate the creation and quality assurance of high-volume, brand-consistent documents.
2. Create dynamic, reusable templates tailored to the firm’s various document types.
3. Have AI modules leverage the firm’s repository of past projects and regulatory references.
4. Fine-tune AI outputs to reflect the company’s unique tone, voice, and branding.
5. Minimize human involvement while maintaining quality and compliance.
6. Provide a scalable solution for diverse documentation needs across multiple clients.

Methodology

Talbot West deployed a CHAI-based solution with a detailed setup process that included:

Template creation

• Document type-specific templates: The team developed modular templates for each document type, such as case studies, reports, and proposals. These templates specified structure, required sections, formatting guidelines, and placeholders for custom content.
• Dynamic adaptability: Templates were designed to accommodate variations in client requirements while maintaining consistency with the firm’s standards.
• Collaborative design process: In close collaboration with the firm, Talbot West ensured templates captured the tone, style, and compliance requirements specific to the organization.

Retrieval-augmented generation (RAG)

• Access to reference libraries: The writer module was integrated with the firm’s repository of case studies, reports, brand guidelines, industry-specific documentation, and regulatory requirements. It used RAG techniques to pull contextually relevant information for document generation.
• Dynamic updates: The RAG mechanism allowed modules to adapt to new or updated references, ensuring outputs remained current and accurate.
• Contextual relevance: By analyzing the prompt and document requirements, the module selected only the most applicable references, avoiding irrelevant or excessive data.

Fine-tuning AI modules

• Custom training on branding: The writer and editor modules were fine-tuned using historical documents to internalize the firm’s voice, tone, and messaging priorities. This ensured outputs aligned with branding guidelines without requiring extensive manual revision.
• Content-specific refinements: Each module was tailored to handle specific document types, allowing for nuanced understanding of the firm’s unique expectations for case studies versus proposals, for instance.
• Iterative improvements: Continuous feedback from human reviewers further refined module performance, particularly in complex areas like industry-specific terminology and regulatory compliance.

Modular workflow

1. Writer module: Generated initial drafts using templates and RAG, ensuring content was well-structured and informed by reference materials.
2. Image generation module: Automatically created visuals aligned with document themes, guided by prompts from the writer module.
3. Editor module: Streamlined content by cutting redundancy, enhancing clarity, and ensuring alignment with branding.
4. Final reviewer module: Performed rigorous quality checks to ensure factual and stylistic integrity.
5. Human-in-the-loop (HITL) interface: Allowed human reviewers to request targeted revisions when necessary, which were quickly executed by relevant modules.

Results

• Time savings: Reduced production time from two weeks (80+ hours) to an average of 20 minutes.
• Resource efficiency: Shifted workload from multiple staff to a single writer and reviewer, freeing up 99% of human effort.
• Enhanced branding consistency: Fine-tuning ensured outputs consistently reflected the firm’s voice and style.
• Scalability: Modular templates and RAG integration enabled rapid adaptation to new client demands and document types.

Challenges and solutions

1. Complex template design: Balancing flexibility with consistency was achieved through iterative collaboration between Talbot West and the firm.
2. Access to diverse reference materials: Ensuring robust RAG performance involved meticulous curation and organization of the firm’s knowledge repository.
3. Initial tuning for branding alignment: Fine-tuning modules required deep analysis of historical outputs, but human feedback accelerated this process.

Lessons learned

• Reusable templates drive efficiency: A well-crafted template library significantly reduced manual effort.
• RAG ensures relevance: Context-aware retrieval allowed AI modules to produce informed and concise documents.
• Fine-tuning builds trust: Training AI on branding materials was critical for stakeholder confidence and adoption.
• A modular architecture (CHAI) outperforms a monolithic solution. For example, a single LLM was unable to reproduce the necessary quality, even when given access to the same knowledge bases and fine-tuned. 

Future implications

This case study demonstrates the scalability and adaptability of CHAI for document-heavy industries. Expanding this approach could include real-time updates for evolving regulatory needs or multilingual capabilities for global markets.

Conclusion

Talbot West’s CHAI implementation streamlined document creation for the consulting firm, cutting production time by 95% while maintaining high-quality outputs. The integration of modular templates, RAG, and fine-tuned AI modules highlights Talbot West’s ability to deliver innovative, scalable solutions tailored to specific business needs.