Artificial Intelligence

Today, there are still very few tools that use Artificial Intelligence to manage real estate assets.

Stonal is the first real estate data management platform to use the full potential of artificial intelligence for asset managers.

Our aim is to harness the power of AI to free asset managers from tedious and time-consuming tasks such as indexing and ensuring the reliability of data relating to physical assets.

Once the property data has been centralised in the Stonal platform, AI also provides real added value in terms of automated reporting, performance indicators and the creation of predictive maintenance action plans.

Artificial intelligence-powered automation can accelerate and simplify real estate asset management processes such as:

• Property data collection and verification:
  Asset managers are responsible for collecting and processing a large amount of data in a wide variety of formats (paper documents, Excel files, data from ERP systems, plans, etc.), which is very time-consuming and tedious. AI can automate these processes by using techniques such as text recognition and automatic natural language processing to extract the relevant information from paper and digital documents. This allows asset managers to save time and focus on higher value-added tasks.
• Predictive maintenance of real estate assets: AI can also play a crucial role in predictive maintenance. By analysing data from sensors and IoT devices embedded in buildings, diagnostics or regulatory checks, asset managers can anticipate maintenance needs, prevent costly breakdowns and extend the life of physical assets.

• Regulatory compliance:
  With a plethora of regulations in the real estate sector, AI is a particularly useful tool for analysing documents such as diagnostics or regulatory controls, checking validity dates or missing items in a portfolio, etc.

  Artificial intelligence in real estate can be used to help asset managers make more informed decisions to ensure compliance with current regulations: safety, health, environmental standards, etc.

  AI does not entirely replace human expertise, but it can certainly complement and improve the processes for gathering information, making data more reliable and therefore making decisions in the real estate industry.

Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on the interaction between computers and natural human language. The main aim of NLP is to enable computers to understand, interpret and generate human language in such a way that they can process the information contained in texts and speeches in the same way as humans do.

NLP uses automatic language processing techniques to accomplish these tasks. This involves the use of statistical models and machine learning.

NLP encompasses a variety of language-related tasks, from the basic understanding of words and sentences to more advanced levels of text analysis and generation.

In short, Natural Language Processing aims to create more natural interactions between computers and humans by enabling machines to understand and generate human language in an intelligent and contextual way.

Asset managers often deal with a large volume of documents, such as tenancy agreements, inspection reports and financial data. Stonal’s platform uses NLP to automatically extract key information from these documents, such as lease terms, contract clauses, important dates and financial data. This saves time and reduces human error.