There are many outdated business practices that are still being used today that are costing money & weighing down your business, and not adding value

The paper-centric business model is one such practice. To record, transact, store, make copies, transport, share, organise, consume, impart, search, etc. all have huge & potentially avoidable costs associated with them

Switch, with Trusted Hub, to a digital-centric business model that works with legally recognised and secure data, and you will be able to divert these monies to support your data & AI transformation to boost productivity.

Talk to us & we will show you how to divert as-is operating funds to begin your data & AI transformation

Data is the lifeline of your business & the "fuel" of all AI solutions. Whether you already have invested in some AI solutions or have not even started, managing data correctly is 100% foundational for all organisations. You need to get this first step right in order to enjoy the fullest potential of any AI solution. Here are the stages of managing your data correctly:

Digitise & Legalise all business data regardless of origin (paper or digital) into legally (Evidence Act)(Electronic Transactions Act) compliant digital data

Organise & Centralise all digital data into correct groupings & host the data electronically, in a legally-compliant and secure way for later consumption

Individualise or Fraternise relevant digital data with proper digital rights control for individual work or team collaboration

Talk to us & we will plan a roadmap tailored for your organisation to manage your data correctly for the age of AI

Data can be used for training AI models, refine as-is AI models or as inference data for pre-trained AI models. No matter how it is used, it must be enriched to enhance its usefulness

Data Preparation for AI Training or Refinement. This process requires data to be categorised, standardised & normalised. This process is critical because the quality of the final trained AI model relies largely on the quality of the data going into the training or refinement process

Data Enrichment for AI Inference. This process requires data to be vectorised. Depending on the data formats (e.g. text, image, audio or video), different vectorisation algorithms will be used to create a multidimensional representation of the original data for retrieval-augmented generation by the AI engine

Footnote: Vectorisation, in the context of data, means transforming data into a vector format. This is often done to make data easier to work with in machine learning and data analysis. When data is vectorised, it's represented as a set of numbers in a vector space, which allows for mathematical operations to be performed on the data more efficiently

Talk to us & we will work out a plan for your organisation to setup a data enrichment strategy that is effective for your AI usage

Mainstream AI primarily works on statistical models to analyze data and learn from data, utilizing techniques like linear regression, logistic regression, decision trees, and more, which allow it to identify patterns and make predictions based on probability distributions within the data

Using this universal method, companies can potentially create their very own AI experts about any aspects of their businesses. Here are some use cases that can be easily set up using Trusted DataVerse, KnowledgeVerse & ActionVerse to bring about exponential gains

AI Advisor / Trainer. Your enterprise data can be digitised, vectorised & mobilized to help address operational issues faced by your front, middle & backend offices, using natural language to talk to your AI advisor

AI Co-Worker. Your staff can easily spin up an AI co-worker to assist them in brainstorming, researching, planning, drafting & refining any aspects of their work, using only specialised, enriched, enterprise data from KnowledgeVerse to assist them

Talk to us about your needs and we will design & configure our Trusted MultiVerse to deliver AI power to your organisation