ARRIA NLG plc is a software development business. Its target is to be the global leader in the development and deployment of mission critical, core industrial, enterprise level Natural Language Generation software technologies. Natural Language Generation (NLG) is the computerised process of analysing and converting Big Data into actionable information.

The Group's core product is known as the Arria NLG Engine.

Global corporations are having to deal with an ever-growing amount of data resulting from the digitisation of transactions and industrial processes and from technological advancements in data capture. Computer networks are now producing and storing digital data at such a rate that this data is becoming increasingly difficult to be fully utilised. This development and the challenge to make optimal use of this data has become known as "Big Data".

The market opportunity for the Arria NLG Engine has grown substantially through the emergence of the Big Data phenomenon.

The Arria NLG Engine is a form of artificial intelligence, specialised in communicating information which is extracted from complex data sources in natural language (i.e. as if written by a human).

The Arria NLG Engine comprises of two main elements:
•an analytics component that is programmed to embody the expert knowledge of the domain in which it operates; and
•a natural language generation component, which embodies the skill required to communicate information articulately using natural language.


This combination of analytics and natural language generation means it can be used to automatically generate written reports in potentially any language for any audience that reads as if written by a person expert in their field. The Directors believe that the Arria NLG Engine provides value where many Big Data analytical tools are limited at the human-machine interface, being the point at which analytic results are communicated to humans.

The Arria NLG Engine automatically communicates results, not in numbers or graphics that may require further analysis and explanation, but in narratives that are designed to read as if written by a human expert. Although it is early days for the Group’s business, its technology is already deployed in a mission critical environment, monitoring large scale industrial machinery located on oil and gas production platforms in deepwater Gulf of Mexico for a major global oil and gas company and at a government national weather service.

The scientific foundation for the Arria NLG Engine has been developed over the past four years, but is based on more than 20 years of research and knowledge gained by the Data2Text Founders at the University of Aberdeen.

In 2009, the University of Aberdeen, Prof. Ehud Reiter, Dr. Yaji Shripada, Ian Davy and John Perry formed Data2Text Limited to develop and commercialise various NLG technologies.

Since 2009, the Data2Text science and technology team has continued to develop the commercial potential of its NLG software technologies culminating in the Arria NLG Engine.

Arria has been working with Data2Text since May 2012 when it acquired a 20 per cent. interest in Data2Text and was granted an option to acquire the remaining 80 per cent. On 25 October 2013 Arria acquired the remaining 80 per cent. of Data2Text.


https://www.arria.com/

Stock Information

https://www.arria.com/investorrelations/keyfacts-A710.php

The ARRIA NLG Engine is monitoring large-scale, mission-critical machinery located on oil and gas production platforms in deepwater Gulf of Mexico

A typical deepwater oil platform is a highly complex, integrated, industrial production facility operating 24/7/365. Its production capabilities depend on a number of large scale rotating machines such as turbines, compressors, pumps, generators and engines. An oil platform operates in one of the most challenging production environments in the world. The production output as well as the safety of the oil platform both depend on the reliable performance of its rotating equipment. When equipment begins to perform outside acceptable operating envelopes, embedded sensors detect the issue and cause alerts to be generated. In addition to rotating equipment, alerts cover a wide range of sources including wells, facilities, and sub-surface equipment. These alerts are monitored by automated systems and highly skilled engineers.

An Example of the Current Monitoring Situation in Complex, Multi-Asset, Surveillance Centres
1.Automated systems monitor data streams and raise alerts.
2. Expert analysts assess whether alerts are valid and need to be further investigated.
3. For valid alerts, the experts write a situational analysis summation which includes context and background.
4. Subject matter experts then further analyse the situation, and create a service recommendation for the equipment.

The problem is that while current monitoring systems generate alerts and notifications, they cannot articulate what has gone wrong. So expert engineers with decades of experience are required to analyse the alerts. But there is such a vast array of equipment generating so many thousands of alerts, it is impossible for human experts to analyse them all. Some control centre operators have likened this data overload experience to “drinking from a fire hose”. Further, the level of expertise required is so high, there is an acute shortage of human experts available to accurately analyse all of the alerts. As a result, alerts are missed and production suffers.

The Arria NLG Engine Effectively Solves This Problem

The Arria NLG Engine effectively becomes the expert. It instantly, automatically, continuously, accurately and effortlessly:
•Reviews every alert even in the absence of the expert.
•Performs analysis that determines what the alerts mean.
• Provides a plain English report identifying which alerts need the expert’s attention and provides the situational awareness that allows the engineer to immediately formulate an action plan to correct the cause of the alerts.

The Arria NLG Engine determines and reports the problem and solution faster than the engineer ever could. It saves each engineer hours of analysis and report writing per day. It works around the clock—never sleeping.1

The ARRIA NLG Engine can write a detailed 3-day weather forecast for 5,000 locations in one minute


Meteorological systems are highly sophisticated with a mass of weather data captured and available as weather changes happen moment by moment across the world. The biggest challenge is the highly skilled human effort of first interpreting this raw weather information, and then writing specific forecasts to inform the general public and industry.

Since 2009, ARRIA PLC has been working with a leading national weather service and others to embed the expertise of weather forecasters into the Arria NLG Engine. To date, the ARRIA NLG Engine™ has been used to create several types of weather reporting:

Site Specific: The ARRIA NLG Engine can be configured to write on-demand, detailed weather forecasts for any site specific purpose in the world such as docking supply boats and flaring excess gas on offshore oil rigs in the North Sea, harvesting on a farm, or even for the weather at the beach you want to go to. In most countries there are tens of thousands of locations of public interest where it would be useful to have a detailed local forecast but, instead, there are only generic forecasts available for big regions like “the south east”, because of the time required to write these forecasts.

Now, our NLG software takes our existing weather service client’s complex raw data inputs and can write a detailed 3-day weather forecast for 5,000 locations within a single minute—and can update them instantly. Right now, our NLG software tackles tasks that would be impossible for forecasters to complete manually. It would take a forecaster 1.5 months to create the equivalent of our system’s one-minute output.

We envision that the ARRIA NLG Engine will be used to generate instant, personalised, localised, on-demand mobile phone content such as our detailed site specific written weather forecasts, to any smart phone user in the world.

Area Specific: The ARRIA NLG Engine can write on-demand weather forecasts for specific geographic areas, and it can also write area specific hazard warnings such as in the complex process of forecasting for gritting and other winter road maintenance procedures.

The Core Arria NLG Weather Engine

Weather reports play a key role in marine, aviation, ground transportation, finance, retail, space and defence. The ARRIA NLG weather reporting technologies benefit these categories. We are currently working with our existing national weather service client to develop a user configurable ARRIA NLG Core Weather Engine. This Engine creates the potential for a completely new weather forecasting paradigm: an NLG Engine that will be able to output on demand, detailed, weather reports for any site, for any area, for any purpose, for any period of time; an NLG Engine with a user-configurable interface that could include:
•Natural Language Output Options that Control:

The grammatical formation of sentences, the variety of the language.

• Format Options:

Written text, annotated graphs and maps, speech.

•Geographic Place Options:

Site specific forecasts, area wide forecasts, point-to-point forecasts, road and surface temperature forecasts (used by the road industry and commercial aviation for runway information).

• Window Options:

24 hour forecasts, 2–5 day forecasts, etc.

• Primary Weather Area Options:

Wind, rain, temperature, etc.

•Primary Market Area Options:

Public, Military, Road, Rail, Retail, Construction, Financial, Commercial and Private Air, Marine.

• Delivery Options:

iPad app, iPhone app, SMS, RSS feeds, websites, fax, email.

NLG Software is helping comfort the parents of babies in neo-natal intensive care


Arria NLG Chief Scientist Ehud Reiter has this vision for NLG in the healthcare field: “One day soon, NLG will be a great empowering tool for people in everyday life, giving them understandable access to medical information about themselves in a form and language that is appropriate for them.”

The BabyTalk research project, an ambitious undertaking of the University of Aberdeen, the University of Edinburgh, others, and a team that included Arria NLG Chief Scientists Ehud Reiter and Yaji Sripada (working as faculty members of the University of Aberdeen), played an important role during the due diligence phase of the acquisition of Data2Text Limited by Arria NLG. It provided a strong proof point in the healthcare vertical and showed the potential NLG technologies have to deliver value in an environment as mission critical as a Neonatal Intensive Care Unit (NICU) at a major hospital.

The BabyTalk case study is included as a case study because it is valuable in the process of understanding the technology. Arria NLG does not own the intellectual property (IP) associated with the BabyTalk Research Project. The IP is the property of the University of Aberdeen. Such IP is an earlier version of NLG which is superseded by the Arria NLG Engine™ technologies. Arria NLG Chief Scientists remain active in the BabyTalk project as academics while Arria NLG staff provide ongoing support services for the BabyTalk modules that are active in the NICU.



BabyTalk: In the Neonatal Intensive Care Unit (NICU), babies are connected to sensors and systems that electronically monitor, record, report and display the condition of each baby. Doctors, nurses and other medical staff are trained to interpret and use this data to aid them in the care of the baby. The data is also used by medical staff to generate a variety of reports such as shift changeover reports and reports to the parents of the baby.

For the BabyTalk project an early version of NLG software was built by the University to: a) embody the expertise of both the medical specialists and the nurses who attend to the babies, b) accept input data from the NICU monitoring systems and c) automatically write three kinds of reports, for three different purposes, from the same digital input data. BabyTalk involved three modules:

BabyTalk Doctor: This module generated written summaries of clinical data over a relatively short period—roughly 45 minutes—to support decision making by doctors and nurses.

• BabyTalk Nurse: This module generated partial shift summaries, focusing on important events related to a baby’s respiration and circulation, in addition to background information, current status and potential problems. Handover is a complex process, and ineffective handover can endanger patient safety. There is no established best practice for handover. BabyTalk Nurse showed that the handover problem is solvable. It showed that an NLG computer system which automatically generates understandable and helpful shift summary texts from a complex, state-of-the-art patient information system holding a large amount of heterogeneous data is viable.

• BabyTalk Family: This module generated easy-to-understand, plain English reports on the medical condition of babies in neonatal care for families. These reports are available online to the infant’s parents, providing a simple summary of their child’s progress. When a newborn baby is admitted to a NICU, parents are frequently overwhelmed by the experience. The neonatal environment in which their baby is looked after can cause feelings of worry, confusion, and helplessness. Parents would often like more information about what is happening to their baby: the baby’s current weight, oxygen levels, milk feeding quantities, and so on. This, coupled with understanding, enables parents to adapt and cope with the situation. This sort of information is important because it helps parents to take on their parental role, as well as get involved with the care of their child’s delicate emotional state. BabyTalk Family solves this problem. It extracts the key facts of interest to parents (which are distinct from the key facts of interest to doctors and nurses), and generates a textual report which humanises the medical facts for parents, presenting them in a way which is both understandable and sensitive to parents. It automatically generates these easy-to-understand reports and makes them available to the infant’s parents online, thus providing easy and immediate access to a simple summary of their child’s progress.

Big Data ,,I kind of get it now , very clever.

:-)) I think posts 21-23 show what an exciting company this is going to be in the future.

leaving the merits of the company to one side, this is a very dificult stock to trade (deal in) ..... the spread is ~10% and furthermore, it is totally controlled by 3 x MMs all of whom will currently only deal in blocks of 1,000

cynic 102m shares in issue do you know the free float percentage?

not off hand, but i'ld bet it isn't more than say 35%

cynic almost spot on admission document states 36.3% interesting explanatory video on their website but very little financial information.

i seem to remember reading that they wanted to get some public exposure or somesuch, and didn't actually need to raise money

cynic was thinking more of EBITDA projections etc

Nearly tripled in value. Rise due to such a shortage of shares, mm's having to lift price. May well fall further to a realistic value. Happy to sit with free shares. I was out for the day and to be honest thought the sp may still rise.

very hard to evaluate "a realistic price" and ditto with WAND, as both are at the very cutting edge of new technology

Wand may as well cynic fall back some more. It has raced ahead of itself of late. :-))

NLG I am only guessing may not drop to a realistic price due to its possible prospects.

on that basis, "a realistic price" could be deemed to be even higher :-)

Is that ramping ? :-)) Just thought I would pose the question. Future Big data prospects have driven WAND.

Pulled this from the company site.

A key objective of Big Data analytics is to enable plain English narratives to be formed which can be used by people to make better decisions and to work more efficiently, adding value to business. Today, this process of producing what is known as "actionable analytics" still depends on intervention by human experts. The shortage of such human experts is a significant limitation on releasing the value locked within Big Data. The Arria NLG Engine has the potential to unlock that value by effectively undertaking the expert's role.

The Arria NLG Engine can automatically communicate its conclusions in actionable plain English narratives which one would believe were written by an expert member of the organisation staff. The Arria NLG Engine is a force multiplier, since, once embodied in software, the expert knowledge can be replicated effectively. This allows the Arria NLG Engine to do the work of many experts, 24 hours a day, seven days a week, 365 days a year.

Shares - Accounts for the year to September 2012 reveal the company made £6.5 million of losses on just £62,554 of revenue. Cranking up commercialisation and boosting recurring sales are the main ambitions for 2014. No new money is being raised at the float as the company secured $40 million of fourth-round funding earlier this month, with a final $6.1 million instalment to be released on attainment of the market quotation.

sp down another 11% are we nearing the bottom?