Aug 22, 2022

Natural language processing (NLP) — Rescuing sales teams

The language used in public calls for tenders is natural for no one. It is often hard to clearly understand the specific services required by potential clients through stiff and complex requirement specifications. What are their needs, and how can we fulfill them? Within very busy sales teams, that question will even be: how can we answer to those needs, fast?

Aloha worked for you, ultimately offering the solution: a platform developed to identify the public calls for tenders that are relevant for your company, list the products to include in your proposals, join the appropriate prices and write out the other pieces of required content based on your previous work. All of this is rendered possible by natural language processing (NLP) based on text, powered by artificial intelligence (AI). Too good to be true? No. Here is why.

NLP: how does it work?

Natural language processing is a concept first examined in order to automate translation in a Cold War context. It was then intended to quickly translate to English parts of Russian speech, without American engineers having to learn the language. Although basic and at times bumpy, this first experiment proved to be promising and encouraged scientists to further explore and promote the field of study. The same period in our History also saw artificial intelligence come forward, leading to great interest for the creation of intelligent computers. After a lengthy introduction of numerous semantical neural networks and elaborate relations between concepts, it is now possible to benefit from the many possibilities offered by NLP. Among them is information extraction from text, particularly interesting in automating your tender bidding process.

In order to better understand how NLP can help your sales teams, watch this short video. It will surely help to materialize the methods used by Aloha to surf in your countless prior documents as to single out and create the right content to include to your proposals.

Implemented in various areas of expertise, many artificial intelligence models used in NLP have proven effective. Here are some relevant examples.

NLP: assisting all fields of work

Legal Field

Let’s first look at the possibilities offered by NLP in the legal field, often using complex vocabulary like the one used in public calls for tenders. Thanks to legal technology (also know as legal tech), AI can understand the meaning of the words used in a text and detect their precise intention. Unlike the first automated translation tools mentioned earlier in this article, it is now possible to grasp semantical subtleties and quickly produce appropriate answers to requirements expressed within the text.

The impressive development of legal tech powered by AI allows for detailed deconstruction of intricate texts, simply substituting human capacities in the production of legal documents (contracts, statements, corporation status), and even in the outright provision of online legal services. This technological breakthrough leads to significant savings, which can only be well received by consumers and companies always looking for faster and cheaper assistance. Bear in mind that these NLP concepts can also be applied to all company management fields, such as accounting, taxation and… sales!

Oil and Gas Field
Photo by Martin Adams on Unsplash

An example very close to our area of interest (efficient production of proposals) has recently made the headlines. The case involves Minestar Groupe Corp., who saw great gains in both time and money, following the implementation of an AI platform used for NLP. This important oil and gas supplier decided to rely on a call for tender advisor based on AI, thus considerably speeding up its bidding process. On the first tries, schedules came from 6 to 9 months down to barely 72 hours. Better yet, the number of winning bids considerably increased. Facing heavy boxes of old proposals, a daunting number of hours required to go through them to find the requested content and an impatient oil market, Minestar Group Corp. opted for technological investment. The implementation of the NLP platform payed off, and the company is now reaping the benefits.

Let’s not forget to mention that the AI tool chosen by Minestar is IBM’s notorious Watson, which can also compete with humans in playing Jeopardy, and is cousin to Deep Blue, which in 1997 won a game of chess against champion Garry Kasparov. These are only some of the countless possibilities offered by NLP, in constant evolution.

NLP: a force to watch out for

It would be inconceivable to conclude without mentioning OpenAI’s astonishing GPT-2 program. This artificial intelligence was conceived to generate text following a logical string of words. Imitating human work almost perfectly and adaptable to various submitted contexts, GPT-2 can produce text respecting style and intention, thanks to its imposing database. Without any need for training in the referred area of expertise, and able to produce in-depth content, the AI can answer specific questions, understand text and further write, summarize and translate it. All that can be done in record time, without supervision or any need for a vacation. GPT-2 is the co-worker we are all dreaming of. Just imagine its potential in producing your company’s proposals. Yes, that’s you on that beach.

This OpenAI program’s extensive possibilities are invaluable. Considered potentially dangerous if misused, GPT-2’s abilities are so wide that its official publication was postponed by scientists. For those of you who wish to know more, the association still released a technical publication, available here.

All previous examples clearly demonstrate how NLP can be used in efficiently automating your company’s proposal process. Other amazing initiatives could have been mentioned, such as Yseop Compose, an automatic text generating software crafted by Yseop, or the work of Eigen Technologies, namely developing NLP for finance.

Nevertheless, experts believe that in order to safeguard AI progress in natural language processing, not only can we rely on the current offer, but we should also ensure growing demand. Let’s be curious and enforce the introduction of such technologies in our corporations, as to benefit from even larger advantages, facilitate our labour, automate our tasks and simply offer clear answers to difficult questions. The only thing left to do then will be to relax to the sound of success. Aloha.

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