Appen has been providing high-quality datasets that power the world's leading AI models for decades. Our end-to-end platform, flexible services and deep expertise ensure the delivery of the high-quality, diverse data that is crucial for building foundation models and enterprise-ready AI applications.

Appen's AI Data Platform supports data annotation, classification, and human preference scoring - alongside model evaluation through A/B testing, user testing, red teaming, and benchmarking, ensuring precise and reliable AI model development. Our platform is ideal for enterprises looking to develop AI that meets rigorous standards.

thumbnail_Appen.jpg

Appen.jpg

Appen

AI as a Service / AIaaS - pronounced "ace" is a platform that ingests and analyses specific known data sets, and then provides output that meets confirmed quality criteria, and provides certainty, where required, with regard to IP sources and ownership.


Generative AI platforms are trained on, and ingest large volumes of data from multiple sources.  The issue with this is that the factual integrity of the input, along with IP ownership of the input cannot be confirmed, which makes commercial usability and value of the output questionable.    

AIaaS platforms give control of the data ingested to the user - e.g. internal corporate documentation and contracts, specific website links - so that the IP ownership is known, the credibility of the sources are confirmed, and accordingly the user can know the allowable commercial use cases of the output.

Vertical AI - AI designed for a specific sector or vertical is typically an example of AIaaS.

AI as a Service - AIaaS

Systems and services related to getting value and competitive advantage from your company data.  Analytics can be descriptive, diagnostic, predictive, or prescriptive.

Data analytics applications include marketing, portfolio, risk, people, software, and digital analytics. 

**Marketing optimisation analytics**

Determining how effective marketing campaigns are and guiding marketing decisions and strategy

**People analytics**

Analysing behavioural data to understand how people are managed, how they perform, and helping improve the Human Resources function within organisations, and ultimately the overall performance of the company itself.

**Portfolio analytics**

Using analytics to understand value and risk in a portfolio - be it of lenders, stock holdings, financial holding etc. - and then drive strategy to minimise risk and optimise returns.

**Digital analytics**

Analysing "digital data" relating to computerised and internet activities.  Digital data includes user clicks, user behaviour, keyword searches, etc.

**Security analytics**

Analysing data either on premise or in the cloud to flag cyber threats, cyber threat actors, cyber attacks, and to deliver post breach forensics on an attack.

Data Analytics

Enabling a company to bring together all its disparate data repositories, so that it can be analysed as a whole, and deliver a single source of truth. 

Data integration

Software applications and associated services dedicated to analysing business information, presenting it in a clear way, so that the right business decisions can be made, and strategies adopted, to seize opportunities, solve problems, and mitigate risks.