
AI is a revolutionary platform combining artificial intelligence (AI) algorithms and machine learning technologies to help organisations create more accurate, efficient, and cost-effective business solutions. AI-driven data analysis can revolutionise today’s business operations by helping organisations measure performance more accurately, improve customer experience, react faster in complex situations, and reduce overall operational costs. By leveraging innovative AI tools such as natural language processing and computer vision, Mostly AI has created a platform that can be used to integrate deep learning capabilities into organisations’ existing workflows.
The primary goal of Mostly AI is to enable businesses to access deep learning capabilities in an accessible and low-cost way to make better decisions based on insights derived from data analysis. Businesses are increasingly looking for ways to use their data assets more efficiently to gain valuable insights into customer behaviour, market trends and product impact while staying agile enough to respond quickly in complex situations. Mostly, AI’s powerful algorithms use techniques such as supervised or unsupervised machine learning models and reinforcement learning methods that leverage sophisticated neural networks architectures.
By providing intelligent automation tools trained with machine learning algorithms combined with human supervision, businesses can make informed decisions faster at lower costs. This technology allows businesses to integrate structured data sources such as transaction logs or sensor readings into actionable insights much faster than manual intervention or traditional analytics processes, enabling quicker decision-making cycles that drive better business results overall. Moreover, leveraging advanced technology such as computer vision can exponentially increase process accuracy while reducing operational costs over time by eliminating false positives arising from manual error cases.
What is Mostly AI?
AI is an AI-powered software platform designed to help companies deliver personalised customer experiences, optimise their operations and increase the accuracy of their predictions. It uses artificial intelligence and machine learning algorithms to provide actionable insights and predictions for organisations.
The platform integrates with existing data sources such as enterprise business intelligence tools, third-party data sources, public datasets, etc. The solution also enables advanced analytics capabilities including natural language processing (NLP), sentiment analysis, predictive modelling and more.

The use of this advanced technology has numerous benefits. Through automated processes that analyse large sets of customer data, Mostly AI can provide decision makers with actionable insights into customer preferences. This can help organisations identify new opportunities and make better decisions faster than ever before.
The platform’s automated recommendations ensure that customers are presented with the most relevant content intuitively, while its predictive models allow organisations to identify areas that need attention quickly and efficiently. Additionally, machine learning can reduce manual labour costs associated with manual processes making it easier for businesses to scale as needed without having a large in-house team dedicated solely to analytics or optimization tasks.
MOSTLY AI raises $25 million to further commercialise synthetic data in Europe and the US
Mostly AI is a platform that enables companies to generate realistic synthetic training data quickly, without relying on costly and time-consuming manual annotation.
Their recent $25 million investment will allow them to further commercialise their synthetic data production in Europe and the US.
In this article, let’s look at some benefits of using Mostly AI’s technology.
Synthetic Data Generation
One of the key benefits to using artificial intelligence (AI) and machine learning (ML) is the ability to generate synthetic data sets. Because AI and ML algorithms require large amounts of training data to produce accurate results, synthetic data generation can alleviate the challenge of procuring accurate and diverse datasets for machine-learning projects. This is especially useful for businesses that are limited by the availability of training data from their internal sources.
Synthetic data generation utilises algorithms to generate realistic, diversified datasets simulating previously collected or non-existent data from sources entirely independent from prior data sources. As a result, it can help create high-quality, privacy compliant, and diverse datasets in much shorter time frames than what would be needed with traditional data collection methods such as surveys and interviews. Using this method, there are also capabilities to have “synthetic twins’ ‘ or exact duplicates of live subjects. Across industries like healthcare, insurance, retail banking, government agencies (e.g., census), and internet services providers, synthetic data generation can provide significant advantages over real datasets by providing a faster path to lower cost AI products development while maintaining compliance with privacy regulations such as HIPAA.
By combining analytics tools with natural language processing (NLP) capabilities along with artificial intelligence libraries such as XGBoost and CNTK that are designed to identify patterns in large volumes of training datasets, it becomes possible for companies to reduce development timetables significantly while suppressing confidential information effectively during model validation testing phases at remote locations for neural network training algorithms groups such as those processes employed by blockchain technology-driven platforms.
Cost Savings
Using Mostly AI can be a great way to save time and money. AI solutions can automate what would otherwise be time-consuming, manual processes, allowing you to allocate your resources more effectively and gain a competitive edge. In addition, by applying AI models to decisions made within an organisation, decision makers can quickly explore different scenarios and fully understand the potential impacts of their decisions before they are finalised.

In addition, using AI reduces the need for manual labour associated with certain processes — saving time and money. By automating repetitive tasks, analytics tools can help organisations focus on key strategic activities instead of mundane manual operations. This leads to faster decision-making, reduced costs from labour savings, increased revenue from improved customer relationships, faster process time — ultimately allowing the organisation to increase its profitability.
AI solutions also assist in predictive analytics — identifying patterns in vast amounts of data that are not visible without machine learning algorithms applied forward them — giving insight into future trends or possible opportunities. This level of early detection is invaluable as it allows companies to make proactive rather than reactive decisions.
Improved Accuracy
Generally speaking, artificial intelligence and machine learning technologies can be used to replace manual processes and improve accuracy. AI systems and machine learning algorithms are designed to learn from data and use that data to predict outcomes with improved accuracy compared to humans. By using mostly AI, businesses can reduce the need for manual labour and instead leverage automated machines to collect, analyse, process and act on data in real-time. This increased accuracy helps businesses make accurate decisions faster, often leading to reduced costs or improved results for certain tasks.
Moreover, AI learns from previous mistakes to avoid repeating them in the future. For example, an AI system specialised in financial analysis may be able to detect potential fraud in a set of transactions faster than humans using fewer resources. In addition, products such as chatbots have benefited from the advancements of AI due their ability to understand more complex customer requests more accurately than a live human customer support representative could do by themselves.
As technologies continue to advance, greater accuracy is achieved through mostly AI-based systems, which provide business owners with invaluable benefits such as cost savings, improved customer service and increased operational efficiency.
Enhanced Security
The primary benefit of using Mostly AI for security is that it can provide heightened levels of protection. Traditional manual methods such as protection from firewalls, malware detection and human intervention cannot keep up with the continually changing threats organisations face today. By leveraging the power of AI algorithms, companies can use predictive capabilities to recognize potential security threats before they become major security incidents.
These algorithms can quickly identify malicious activities which could be used to increase the accuracy and efficiency of investigations undertaken by organisations. Machine learning technologies can not only accurately identify suspicious activities in real-time, but provide recommendations for countermeasures which greatly reduces the amount of manual labour involved in dealing with cybercrime concerns. Moreover, advanced AI-based solutions can work within an organisation’s existing system environment rather than creating a new one, which allows organisations to benefit from increased protection while reducing overall costs.
Recent Funding
Recently, MOSTLY AI, a synthetic data company, closed a $25 million Series A funding round to further its mission of commercialising synthetic data in Europe and the US. This funding will help expand MOSTLY AI’s presence in these regions and drive the adoption of synthetic data across enterprises.
Let’s look at what this funding could mean for the future of synthetic data.
Overview
Mostly AI is a machine learning and artificial intelligence company that is revolutionising how businesses harness insights from natural language. Powered by Deep Learning, they have created the world’s first modularized AI platform that provides enterprises access to automated sentiment analysis, predictive analytics and natural language understanding (NLU).

Recently, Mostly AI has secured a Series A funding round of $4.4M from investors including Denwalt Venture Capital, Innovation Nest and FertiFunds. This new funding will enable them to continue developing their cutting edge technology and expand into new markets.
The benefits of Mostly AI include access to advanced analytics tools such as predictive modelling, the ability to identify unstructured data from text sources such as web pages or emails, automated sentiment analysis for improved customer feedback tracking and NLU for easy integration into existing applications or platforms. Additionally, their modularized platform allows for custom development, giving organisations flexible solutions that can be optimised according to specific requirements.
Impact of Funding
Most AI’s recent funding is likely to have immediate and long-term impacts. The most important benefit of the investment is expected to be Mostly AI’s ability to hire more personnel and further develop their solutions while expanding their markets. As the technology behind AI evolves, so too will the abilities and capabilities of their products.
Adding new talent will also allow Mostly AI to canvas more markets for revenue opportunities. With improvements in accuracy, speed, and scalability – thanks to increased funding – AI is expected to become more marketable across global industries from logistics, agriculture, finance and beyond.
It was also announced that some of the funds raised will go towards developing new software-as-a-service (SaaS) models for specific industry solutions like autonomous vehicle technology, smart grids development etc. This suggests that the company intends to move away from its core business model in terms of capitalising on its current value proposition while simultaneously focusing on branching out into other areas. This could prove beneficial in continuing the evolution of the product portfolio while simultaneously increasing customer satisfaction levels.
Overall, it can be discerned that with added resources Mostly AI can move forward at a faster operational pace compared to previous years; this opening up room for strategic product innovations as well as solutions at an international level which can thus open up further potential markets or niche opportunities where businesses seeking automation & optimization solutions may find appeal in customers needs being met quicker & better than before given these developments with newly acquired resources & personnel achieved through recent funding agreements.
tags = raises $25 million, MOSTLY AI, commercialize synthetic data, Europe and the US, artificial intelligence, mostly ai molten venturessharmaventurebeat, Tobias Hann, founded in Vienna in 2017, General Data Protection Regulation