Art Objects’ Valuation

Equip art object owners and dealers with a solution that is capable to make real-time valuations of their works of art.

We designed a platform that boasts a real-time database fed with art deals. On the basis of the data received, the system simulates human expert decision making process to evaluate art objects. As the output, end users get an estimated priсe for their art objects. This is an instantaneous process that takes into consideration all art trades available online.

Functional elements of the platform include:

1. Web App: This is a client-side interface, where end users can add their art objects, get real-time valuation of their artworks, track auction events, follow the news on tradable works of art, keep themselves updated as to the market trends, etc.
2. DB: This is our validated and verified database. It accumulates real-time information about all art deals for the data team to check their relevance (e.g.an art object’s year and size, information about the artist, the currency of the deal, etc.).

Our algorithms add selling value!

The decision-making process of the platform’s algorithms is modeled similar to the evaluation a real expert would perform: the current market value of an art piece is taken into consideration along with the value of this or that artist’s works according to the latest market trends based on social and political news. This in turn equips the platform’s users to pick up the best moment in time to buy or sell their art assets.

Additional features for best UX

The process of art objects management via our platform gets more efficient due to these features our team has delivered:

• Art dealers can perform evaluations remotely and in a time- and resources-efficient manner;
• Art managers can assist more clients and grow their business sufficiently;
• Art dealers can easily open access to the platform’s UI for their clients to share with them thelogic of their evaluation decisions, which builds trust;
• Asset management companies can get better margins for art trades with the help of the real-time evaluations of artworks and the system’s capacity to track the market.
• The ML algorithms of our solution eliminate possible human-factor risks when evaluating art pieces.

Technology applied

CPCS engineers applied the following technology and methods:

• Mathematical modelling (simulations)
• Machine Learning
• Pattern recognition
• Data analysis
• Neural networks (deep learning, classification)
• Data visualization
• Natural Language Processing
• Decision trees
• Ensemble modeling
• Fuzzy logic

Customization

The solution’s algorithms are customizable for varied business needs. This needs should embrace the following conditions:

1. your valuation process is time-consuming and costly;
2. the data which influences your decisions could be both obtained from open sources and classified;
3. your industry is Real Estate, Automotive, Insurance, etc.
4. your business needs a cloud solution instead of a web app, which is also doable.