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Q for Business

Harness the power of Generative AI Retrieval-Augmented Generation (RAG) for your business.

What is Q for Business?

Q for Business is a cloud native Generative AI assistant tailored specifically to a customer’s individual needs. Q can be trained on company specific data sets to super-charge sales, marketing and operational teams.

Whilst tooling exists to enable organisations to build similar capabilities, self-building presents challenges such as the necessity for internal expertise in LLM architectures and frameworks, expenses related to hardware and software, ongoing maintenance and operational needs, security and compliance considerations, and data management challenges including versioning and re-indexing to maintain the assistant’s ongoing accuracy.

Q for Business Accelerator 

Rapidly pilot and explore the benefits of Gen-AI for business with off the shelf templates and our expertise in building custom AI solutions.

Organisations with internal domain-specific knowledge bases; for example, standard operating procedures and market intelligence. 

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  • Boost team productivity: Q for Business streamlines workflow by summarising documents, generating drafts, conducting research, or running comparative analysis.
  • Tailored to your needs: Q connects to company information, allowing it to generate content and take actions relevant to your business.
  • Secure and compliant: Q understands and respects existing role and permission structures and boundaries, enabling customers to meet their most stringent enterprise compliance needs.
  • Dramatically reduce code and infrastructure: Compared to self-build, a Q implementation has a far lower implementation and maintenance overhead, reducing TCO.
  • Always improving: The LLM technology backing Q is constantly evolving, meaning that improvements can be incrementally deployed at low cost.
  • Sustainability: Using centrally trained and managed models, as opposed to self-training Q improves your company’s carbon footprint.
  • Cost efficiency: By leveraging AWS Funding Programs, we
    minimise customer costs for the Accelerator.
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The Process:


The Q Accelerator begins with an initial discovery workshop which typically takes one day. The workshop aims to identify high-business value use cases. Following the workshop, we determine which of the identified use cases to pilot based on the availability of data, security and compliance requirements and end-user needs. We also determine a set of objective business KPIs to measure during the pilot. In total, this phase takes approximately one week.


During the pilot phase, we configure and deploy the Q application(s) and the associated infrastructure required to connect to data sources and end users securely and measure the identified KPIs. Deployment of the pilot typically takes two to three weeks. We then allow time for users to engage with the assistant to collect feedback.

Plan & Rollout

Objective KPIs are measured and, along with subjective user feedback we evaluate the business impact of the pilot. Based on these measurements we determine a rollout plan to move to a full production implementation. The plan typically addresses data security, classification, versioning and role-based access issues.
The AI-Powered Underwriting Assistant

Developed by Describe Data and fourTheorem, Augmented Underwriting taps into two decades of Lloyd’s Market Bulletin expertise. Query, explain, and summarise effortlessly for sharper insights and faster decisions.

How does it work? We have trained our AI to understand and summarise insurance-focused documents such as submissions, and regulatory and compliance documentation. Try it out now on the Lloyd’s Market Bulletins with a sample query, such as, ‘Tell me about the current changes in regulations governing letters of credit?”.

With a sample of your unstructured documents, such as insurance submissions, we will build you an underwriting AI assistant tailored for your business.

Why fourTheorem? We wrote the book on it. 

We took our experience of Serverless, AI and Machine Learning technologies to create an engineers guide to artificial intelligence.

AI as a Service is a detailed guide to operationalising Cloud Native AI Services on AWS. As an Advanced Consulting Partner, we have architected and delivered systems for our customers that harness the power of AWS AI services.

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Have a Question

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