LLM Automations

Reimagine workflows to become more purposeful

The potential of Generative AI (GenAI) automation using large language models (LLMs) is immense, yet identifying the most transformative project for your business can be challenging. These projects should be bold yet realistic, and form a part of your overall GenAI strategy. LLMs, with features such as retrieval-augmented generation (RAG), multilingual support, and the ability to connect your organisation’s data, present numerous innovative automation opportunities.

Potential improvements

  1. 10-20% EBITDA uplift
  2. Talent development and retention
  3. Faster time-to-decision

However, just because something can be automated doesn’t mean it should be. Businesses need to rethink problems and reimagine workflows to uncover AI use cases that extend beyond current tasks and unlock new value — what Re:Adapt refers to as “augmented expertise”. We begin by identifying with clients their “best start” LLM automations and adopt an experimental approach.

5 LLM Automation examples

1. Automated Document Processing

LLMs can automate the creation, review, and approval of documents, such as contracts, reports, and compliance paperwork, reducing manual effort and accelerating document workflows. LLMs can extract information, help you review documents, generate reports, and interact with your documents.

Ask us about: designing better document workflows.

2. Data Analysis and Reporting

LLMs can analyse large datasets, generate insights, and produce comprehensive reports, aiding decision-making processes within enterprises.

Ask us about: building a data analyst AI agent.

3. Advanced Financial Analysis  

Enterprises can automate financial, operational, and tabular data analysis by leveraging LLMs to evaluate various factors and generate reports. Equip your LLM with capabilities that help you analyse spreadsheets and financial data.

Ask us about: building a financial analysis AI agent.

4. Automated Sales Operations

LLMs can facilitate seamless communication between APIs, enhancing customer support by integrating with existing CRM tools. For example, maintain your CRM by automatically analysing sales call transcripts.

Ask us about: building AI augmented sales workflows.

5. Enhanced Tech Support

Integrating LLMs into support systems to handle complex queries, provide detailed responses, and escalate issues as needed significantly improves customer service efficiency and satisfaction.

Ask us about: building a Q&A chatbot from technical documentation.

Experimenting with LLM automations and collaborating with interdisciplinary, diverse, and cross-functional teams can lead to groundbreaking enterprise innovation. Large R&D budgets are not necessary to achieve this. The cross-pollination of ideas, combined with scalable GenAI automation that supports enterprise workloads, is the foundation for reinventing work.

The first step is to discuss your interests; email us at contact@readapt.science to set up a call.