Natural language processing algorithms are too expensive for many smaller businesses – Kuldat offers a data analysis alternative
Kuldat announced on Thursday that it has raised $1.5 million in Series A funding from Italian tech VC United Ventures. The startup, founded in 2012 by data scientist Marco Visibelli and based in Boston, is a big data platform that utilizes artificial intelligence to catalogue, process, and analyze information to simplify and streamline marketing and sales.
Visibelli told Geektime in an interview that Kuldat intends to bring big data analysis to smaller companies that historically could not afford it. He said, “The company’s goal is to find the perfect lead for each customer without human intervention.” He explained that for many companies, the sales process is still what it was 20 years ago; people search for leads, and too much of the work is done by hand. With its cloud based system, Kuldat wishes to connect SMEs cheaply and quickly with potential clients from all over the world.
Improving big data analysis, and more importantly, making it affordable
Swaths of consumer data are collected daily by mobile phones and from social media, shopping, and entertainment websites. But to make this explosion of big data sources relevant, artificial intelligence must also advance to make meaning out of sheer data. Thus, it comes as no surprise that BBC Research predicts the market for smart machines, which was valued at $6.2 billion in 2014, to grow at a five-year compound annual growth rate of 19.7% to $15.3 billion by 2019.
Often, consumer data is analyzed using natural language processing algorithms. However these algorithms are very expensive to employ, often outside the acceptable sales budget for SMEs, and, according to Visibelli, have some limitations. Kuldat set out to solve this problem and give SMEs access to data analysis that can connect them with customers around the globe, especially in relatively untapped and unknown markets where human sales probing might not reach.
On his company’s solution, Visibelli explained to Geektime, “Natural language processing has some limits, mostly related to the incompleteness of the available multilingual text corpora. Kuldat tries to overcome these limits by combining several data sources using a proprietary algorithm specifically designed to provide a valid relevance indicator for target documents, regardless of their topic.” If that meant nothing to you at all, essentially Kuldat employs a cognitive technology that processes data from 25 industries, six markets, over 250,00 companies, and 15 million daily online messages to identify the unsatisfied needs of certain under tapped markets first, and then target potential clients.
To make this data processing affordable, Kuldat relies on the cloud. Visibelli said, “We have a single ‘instance’ of the system that is shared among different customers. All the infrastructure is created in the cloud so we are able to scale up the system when the users increase.”
Kuldat plans to use this funding round to expand globally and continually update its technologies to stay relevant within its quickly moving field. Visibelli told Geektime that his company wishes to expand specifically into the U.S. market, where it believes SMEs have less access to big data analysis, especially in the field of sales and marketing. Visibelli also said his company plans to service Asian markets where demand from industrial companies, which make up a large portion of Kuldat’s clientele, is mainly untapped. Kuldat also plans to release its integration with CRM (customer relationship management) platforms such as Salesforce in September 2015, and to integrate its system with Microsoft Dynamics and SAP CRM afterwards.
How does it compare against the competition?
Kuldat seems to provide value with its simplicity and price point. However, Kuldat’s singular goal is to use big data analysis to give its clients more customers. Other market intelligence firms take the approach a bit further by using big data to monitor CRM in real-time. Market research company CustomerMatrix is one of the first to apply cognitive intelligence to CRM. Also, other firms provide more support in brand growth. Market research firm Radius leverages big data to find customers, but also provides support in a variety of other brand related dimensions, like pricing and message optimization. Furthermore, it analyzes qualitative aspects of consumer behavior to create a more rounded pitch.
The key strengths of Kuldat’s system is its affordability and simplicity, but to compete in the market intelligence field, it must integrate more CRM systems quickly and prove the effectiveness of its one-pronged, algorithmic approach to customer acquisition.