Matt Shearer

Data Language is proud to be featured in the "AI for Business" supplement in The
Times (10th December 2020). 

This supplement covers a range of AI solutions across a spectrum of enterprise
use cases.

To implement AI successfully
 1. You need a consistent source of reliable data to feed the AI systems.
 2. You need leadership within the organisation who understand the need to make
    faster, data-driven decisions.

The Times : "AI for Business" - 10th December 2020.Read more
 1. Raconteur AI Section
    [https://www.raconteur.net/topic/technology/artificial-intelligence/]
 2. Data Language Explainable AI Platform
    [https://datalanguage.com/products/datalanguageai/explainable-ai-platform]
 3. Data Language Text AI Services
    [https://datalanguage.com/products/datalanguageai/text-ai-services]

The Times "AI for Business" Supplement

Data Language AI for News offers a new market-leading automated news classification SaaS. It beats other SaaS because it uses your own tags.

Data Language AI for News - Automated News Content Classification

Automatically Tag your text with News Tags
We’ve trained our Data Language Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] using a News
training corpus, and are making it available for you to try out.

Simply add your text, and get News tags back. Get the latest News tags,
consistently, and improve your user journeys and SEO.

Industry-leading Auto-tagging AI
Our sophisticated Text AI automated classification service
[https://datalanguage.com/products/datalanguageai/text-ai-services] is designed
with years of experience in Data Science. It beats popular benchmarks, and
tackles all the normal data science issues faced with News auto-tagging.

Get access
Simply use the contact form to request access.

News, features and updates about our Data Language AI Products. Find out how our AI Products solve common specialist and scaling problems.

News, features and updates about our Data Language AI Products. Find out how our AI Products solve common digital transformation challenges.

Data Language AI - News and AI Product Updates

Data Language AI

Data Language AI for News - Automated News Classification

We work with organisations to deliver their ambitious production AI projects,
and we understand the need for speed, and for managing total cost of ownership.

Avoid getting stuck in "Proof of Concept" phase
In a recent survey of 1,093 industry professionals by Forbes, 64% of respondents
agree that the challenges of implementing AI have been underestimated. 61% of
the same group agree that many AI projects were having trouble getting beyond
Proof of Concept and prototyping stages.

Deliver production value, quickly and early
At Data Language, we have seen all the common issues in the design,
implementation and scaling of AI systems, and we can help you through this
process. We specialise in delivering valuable MVPs quickly and early.

Let's talk
Get in touch with us for a free assessment - we are here to help!

Delivering a Scalable AI MVP

Paul Wilton

"SCOPA" is the original name for our Explainable AI Platform that provides high throughput, scalable, explainable predictive analytics. 

Explainable AI Platform - SCOPA - for high volume specialized XAI

"SCOPA" is the original name for our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] that
provides high throughput, scalable, explainable predictive analytics.

SCOPA is now called Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] 
Our platform allows us to deploy a suite of layered deep learning, ML, and
algorithmic models, in an ensemble. The results of this can be reasoned-upon to
answer very subjective questions about the input data holistically.  Models and
algorithms are individually scalable, and each may identify or predict a
specific outcome, but collectively they can answer more holistic questions. The
orchestration of the models, data analysis and pipelining is contained and
managed within the Explainable AI Platform.

Explainable AI Platform Features
Why "Explainable AI"?
AI should not be a black box. To engender trust it is imperative that consumers
of machine learning predictive analytics understand how the AI reached its
decision.

Whether for decision support or as a decision maker, an AI application must be
able to explain itself and be accountable.

Explainable AI (XAI
[https://en.wikipedia.org/wiki/Explainable_artificial_intelligence]) is a
burgeoning field in machine learning that tackles this challenge, so we, as
ultimate end-users, have faith in machine intelligence and can strive for its
continuous improvement. Our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] 
embraces explainability, providing insights into the decision making process of
the predictive output that it has made in answering questions of the data,
ultimately providing a fingerprint of the predictive qualities.

Scalable
Our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] is
built for scalability. Every model or algorithm deployed into the platform is
containerised and individually scalable. Queuing and constraint theory allows us
to dynamically scale models at every step in a prediction pipeline based on the
performance and throughput required of that model.

Evolvable
Evolvability has been baked into the architecture as a 1st class concern
providing a high degree of potential for customisation and extension. This makes
it an extremely portable solution across diverse domains, and also allows the
predictive model architecture to evolve as the problem space changes over time.

Deployable
Our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] is
deployable in cloud or on-premises, and can be used either on a fully managed
SaaS basis or as an enterprise self-managed deployment in your own
infrastructure. It also uses contemporary open-source architecture technologies,
with full deployment automation. It can even be deployed on laptops for
demonstrations or at-the-edge applications.

Use Cases
Our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] is
ideally suited to enterprise use-cases in a number of sectors, such as
specialised media classification, industrial maintenance, agri-tech, and
healthcare.

It has been deployed to classify terrorist and extremist propaganda imagery for
the security services and the Home Office in the UK at scale. 
Even for such a complex and multi-faceted challenge, a bare bones instance of it
scored remarkable metrics (over 0.95 precision, 0.85 recall) with plenty of room
for substantial improvement.

Our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] can
be deployed for use cases in industry such as railway track environment analysis
, or for predictive maintenance.

In Agri-Tech is is suited to use-cases such as crop disease prediction, yield
prediction, or pest analysis using for example, drone footage, or spraying-boom
camera imagery.

In healthcare it can be used for novel image analysis such as bone fracture
detection. 

Please do get in touch if you would like to find out more.

SCOPA - scalable, explainable AI

Our Text AI Services for Publishers provides auto classification, recommendations and entity extraction. The engineering and data science is taken care of.

Text AI Services for Publishers - highly optimized scalable AI

Our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] were
originally designed to meet the challenges of automated content workflows in the
publishing industry, and are ideally suited to classification and tagging of
news, sport and entertainment content.

Why do publishers tag their content?
Most large publishers need to tag or classify their content for a number of
reasons :

 * to assist internal processes and work-flows
 * to improve search and discovery
 * to provide richer content and user analytics
 * to drive advertising
 * to deliver richer user experiences

Typically tagging is a manual task, integrated into the editorial workflow and
the CMS. Increasingly, publishers are working to automate this process using NLP
and machine learning techniques.

Automated content tagging
Automating content tagging unlocks a lot more value, as the automated-tagging
system can be used to

 * improve tagging efficiency, consistency and quality on the news desks
 * fully-automate tagging of external news feeds
 * unlock value in long-tail content
 * automate tagging of other content around the organisation

For this reasons, publishers are investing large sums and time in building their
own automated tagging systems. However what may seem like a simple problem in
the R&D labs can turn into a much more complex and expensive problem, when put
into production.

How Data Language Text AI Services can help
O [https://datalanguage.com/tagmatic]ur Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] are an AI
and Machine Learning fully managed SaaS product. We built them to make it as
simple as possible to integrate automated tagging and classification into your
publishing systems, addressing all the key challenges :

 1. It is incredibly easy to integrate. Send it content to learn. Send it
    content to tag.
 2. It uses your own dictionaries, taxonomies, and classification vocabularies
    out of the box.
 3. The engineering challenge of scaling, retraining, and efficiently
    redeploying the machine learning models is done for you.
 4. It learns on the fly. As new terms arise in news, our Text AI Services
    [https://datalanguage.com/products/datalanguageai/text-ai-services] learn
    them quickly.

Total cost of ownership
Building you own AI based tagging solution is no mean feat. It is not just a
data science problem, but involves software engineering, testers, DevOps,
infrastructure, scaling automation, model deployment automation, continuous
machine learning model training automation, as well as the project management
and business processes that accompany a project of this nature. Both the total
cost of ownership and time-to-deliver is substantial.

With our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] you can be
up and running in hours, not months, at a fraction of the total cost and you can
put your data scientists to work on your market differentiating data outcomes
instead.

Get in touch
Use the contact form to get in touch - we are here to help.

News and product updates about our Text AI Services. Read about how our Text AI products are being used in innovation projects, and by our clients.

Read the latest on our Text AI Services. Projects, Innovation initiatives, and new developments for AI features in specialized use cases.

News and Product Updates about our Text AI Services

Text AI Services

Text AI Services for Publishers

Tolga Ergin

A great AI or ML model is worthless if it can't be delivered in a scalable, cost effective and technically sustainable way. Find out how.

Data Science at Scale - 10% AI, 90% Engineering

A great AI or ML model is worthless if it can't be delivered in a scalable, cost
effective and technically sustainable way. Our data science team excels in the
design and implementation of machine and deep learning models for the analysis
of data and media at scale.

Data Science seems to have something mystical about it, to the extent that
enterprises have almost come to consider it as a magical solution to impossible
problems. The reality is that behind DS there are tons of unfashionable data
engineering and analysis tasks, before statistical models can be applied to the
problem. 

Our team of talented experts here at Data Language can leverage years' worth of
technical excellence to ensure your AI solution can actually be scaled and
delivered at the highest standards of software engineering.

Understand your data 
Unlock the full potential of your data through early discovery, analysis, and
visualisation.

Learn fast
With so many variables to tweak, rapid feedback and short iteration cycles are
imperative to an effective delivery.

Models are software
As with any piece of code, statistical models also benefit from engineering best
practices for delivering at scale, with controlled total cost of ownership.

--

Read our white paper on rethinking how you do data science in your organisation:

 
[https://datalanguage.com/static/whitepapers/rethinking-data-science-in-the-enterprise.pdf]

Data Science at Scale

We are developing our Text AI Media Classification Products to help Cochrane automatically classify Clinical Studies onto Snomed-CT and PICO structured data

AI Classification of Clinical Studies with Text AI to fight Covid-19

We've just received the green light on this public-funded innovation project,
bringing two areas of significant Data Language expertise into play to help
combat Covid-19.

The mission combines two of our favourite things:
1. Clinical Evidence Knowledge Graphs
We've been working with Cochrane on their knowledge graph and data strategy
[https://datalanguage.com/blog/how-knowledge-graph-technology-is-helping-cochrane-respond-to-covid-19] 
since we started the project with them in 2014. As part of this, we recently
helped them launch their Covid-19 Study Register
[https://datalanguage.com/blog/covid-19-rapid-response-technical-delivery-at-cochrane]
, which summarises the current state of Covid-19 clinical evidence from around
the world that has been released into the public domain via authoritative trial
registries and journal databases.

2. Our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] for
automated text classification
Over that time, we have also cemented our position as industry leaders in
machine learning text classification and analytics, and have developed
particular expertise in high volatility domains (e.g. academic research,
breaking news, R&D) and complex ML engineering challenges. This led us to
creating our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services].
[https://datalanguage.com/tagmatic-ai-document-classification]

Mission: to ensure Covid-19 clinical decision making is informed by the latest,
most comprehensive reliable evidence possible.
With the help of the UKRI [https://www.ukri.org/], Digital Catapult's Machine
Intelligence Garage
[https://www.digicatapult.org.uk/for-startups/acceleration-programmes/machine-intelligence-garage]
, and Innovate UK [https://www.gov.uk/government/organisations/innovate-uk], we
are now bringing our Text AI Services
[https://datalanguage.com/products/datalanguageai/text-ai-services] into play
with our subject matter expert partner Cochrane to help the fight against
Covid-19.

We will be launching this new HealthTech AI beta before December. 

Get in touch if you want to know more.

Automated Classification of Healthcare Evidence

Our pitch included using our Explainable AI Platform to provide London's analysts with explainable AI (XAI) decision support.

Explainable AI Platform at London Civic Innovation Challenge

We've just been at City Hall for London's Civic Innovation Challenge Awards
Ceremony. Sadly we didn't win on this occasion, but we were proud to be in the
finalists for the Counter Violent Extremism Social Tech Challenge.

Explainable AI Social Tech to help Londoners
Our pitch included using our Explainable AI Platform
[https://datalanguage.com/products/datalanguageai/explainable-ai-platform] to
provide London's analysts with explainable AI (XAI) decision support.

Explainable AI decision support - in this case for violent extremism specialists
Thanks to the GLA Team and Social Tech Trust!
The finalists with the GLA team and Social Tech Trust.

News and Product Updates about our Explainable AI Platform (XAI)

Explainable AI (XAI) means that the process, reasoning and decisions made by the AI are transparent and clear to the users and teams involved. Even before this became a trending technical jargon term, we were delivering Explainable AI products and services.

Updates and news about our Explainable AI Platform (XAI). We are specialised in moving new AI services to production rapidly, avoiding pain points in XAI

News and Product Updates about our Explainable AI Platform (XAI)

Explainable AI Platform

Proud Finalists in London's 2020 Civic Innovation Challenge

Fill out the form and we will get back to you shortly.

Get in touch

Our Explainable AI Platform provides insightful decision support using mixed media and data predictive analytics, a specialized area where Data Language leads the way.

Provide explainability at scale, rapidly

We orchestrate ensembles of predictive analytics models to answer complex questions

Answers Complex Questions

The AI and ML engineering and scaling is done for you: DevOps, DataOps and ModelOps

Production Ready

Designed to be rapidly evolvable, so that you can adapt to new scenarios with ease

Evolvable

The ML model ensembles provide a transparent decomposition of each decision

Explainable

According to Gartner Inc, only 53% of projects make it from artificial intelligence (AI) prototypes to production. Use our AI products to avoid the common pitfalls and unforeseen difficulties in ModelOps, DataOps and DevOps.

Get AI into production, rapidly

Achieve high accuracy, agility and explainability for use cases that require specialized predictive analytics

Explainable AI Platform

Answer complex questions in computer vision, media classification and data analysis.

Get in touch

Related Blog Posts

Related Work