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How Large Language Models (LLMs) can add leverage to your business

Applications such as ChatGPT and Claude have exploded in popularity across the digital landscape - and for good reason. Being LLMs that can generate insightful recommendations and automate tasks in an intelligent manner, much potential lies for organisations to embrace these and other AI-powered tools, such as LLMs and Natural Language Processing (NLP).

Also classified as Generative Artificial Intelligence (GenAI), the likes of ChatGPT and Claude are accessible to organisations across any industry or size. In fact, not embracing AI-powered technologies such as GenAI, LLMs or NLP could entail the risk of businesses lagging behind - especially as competitors leverage the same to impress customers.  

Research by McKinsey estimates that Generative AI could add $2.6 to $4.4 trillion in value across the global economy, especially in areas such as customer operations, sales and marketing, and software engineering.

A few prime examples of how this value is created includes:

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Enhancing the quality of, and context behind, customer interactions (both human and automated).

Optimising sales and marketing reports with forecasts that are accurate as they are intelligent.

Maximising productivity across the workforce, while reducing costs at the same time

With GenAI doing so much, it’s no wonder that many of the world’s top tech companies are investing heavily into GenAI research. Similar to how the internet completely transformed how we communicate and connect today, GenAI’s abilities to automate repetitive tasks, alleviate the possibility of human error, as well as deliver personalised content and recommendations has become a game-changer for the companies that have already adopted it.

Advanced data modelling and prompt engineering, for uncovering deep, granular insights

Personalised user experiences and recommendations, through conversational AI

Zero-shot, one-shot and few-shot learning methods, for faster yet accurate model training

Intelligent workflow automation, to eliminate manual intervention and bottlenecks

Optimised risk monitoring and mitigation, for compliance and cybersecurity

Enhanced R&D and product innovation, across any niche - horizontal or vertical

How can EFutures help with GenAI?

With long-standing expertise across multiple domains, our AI teams deliver subject matter knowledge that has been garnered through hands-on experience working with leading GenAI applications.

As a result, EFutures can enable your business to implement GenAI through:

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What sets EFutures apart?

We know that building, deploying and monitoring GenAI models isn’t infallible; complexities and challenges abound in a space that incorporates vast datasets and advanced algorithms.

Our AI specialists understand this, which is why our teams work proactively to contain challenges surrounding data, prompts and labelling strategies - while researching for newer, innovative ways to tackle persisting problems too.  

Additionally, maintaining a strict sense of responsibility is also top priority for our teams, so we can deliver GenAI that leverages bottom line growth for your business, while being well within the boundaries of ethics and compliance.

At EFutures, our AI teams help your business mitigate an array of GenAI challenges surrounding:


Data transformation, which includes (but isn’t limited to) splitting and fine-tuning

Token limits

Raw and unfiltered datasets

Concerns around ethics, integrity and biases

Combined with our expertise in custom software and application development, our teams here at EFutures can deliver a holistic solution that’s power-packed with intelligent, AI-driven capabilities - while evolving to suit new technologies, as they appear.

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Our partnerships with Microsoft and AWS - and what this means for our clientele.

Although publicly facing GenAI and LLM applications such as ChatGPT may be highly accessible for delivering quick results, these can significantly increase vulnerabilities for your organisation. A lack of data security is the biggest factor to consider here, as confidential information could be fed into publicly available LLM models by employees (both knowingly and unknowingly).

Implementing private LLM models is a viable solution, as it mitigates the risk of data leakage, while maintaining models that are custom-trained to exclusively address the unique needs of your organisation.  

As a Microsoft and AWS partner, EFutures has the capabilities to build private LLM models at scale. Through Microsoft’s partnership with OpenAI, and AWS offering Claude via its partnership with Anthropic, EFutures can train, build and maintain private LLM and GenAI models to suit each client’s specific requirements.

Along with purpose-built customisation, our partnerships with Microsoft and AWS shall also deliver:

Advanced data security and comprehensive audit trails, to stringently meet a wide variety of compliance needs,

Comprehensive Identity and Access Management, via MFA and granular access controls,

Hosted infrastructure for LLM models that can scale up or down with near-zero downtime.

While our AI teams here at EFutures place great emphasis on working in close conjunction with the standards set by Microsoft and AWS, our experts also utilise other tools such as GitHub Copilot, to further strengthen the quality and accuracy of custom algorithms.

Our AI adoption roadmap

As AI proliferates across today’s digital landscape and automates numerous processes across organisations, concerns are raised about deskilling and redundancies. However, the skills now required in job roles are expected to evolve, in order to ensure working professionals can expertly function alongside AI-powered systems - akin to getting familiarised with Microsoft Office tools at the height of the digitisation era.

  At EFutures, our teams understand that building AI models goes beyond only meeting business bottom lines. As a result, our AI expertise extends beyond technical areas, to also address social concerns surrounding AI adoption.

Technical and otherwise, the entire scope of our AI services include:

Educating business teams on the potential and possibilities of AI

Strategically identifying use cases that are contextually relevant for AI adoption

Building MVPs to encourage a gradual adoption of intelligent technologies (especially for pilots)

Enterprise-wide implementation as well as post-implementation strategies

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With AI beckoning more than just technological advancement, our team of AI experts will ensure that all your business concerns are addressed with an AI adoption roadmap that is tailored to exclusively meet the needs of your organisation - no matter how unique they may be.

Reach out and connect with us!

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