Spectra Analytics are a leading Artificial Intelligence (AI) software company. We have been providing AI-as-a-Service (AIaaS) for over 5 years across multiple industries.
Companies are under increasing pressure to develop AI solutions to i) make sense of all the data they are collecting, ii) drive increases in efficiency and productivity, iii) improve insights for users, and iv) to differentiate their products.
However, many companies have found that developing their own AI solutions is extremely difficult. 50% of AI projects fail and only 20% move beyond the Proof of Concept stage. This is generally because they do not have sufficient AI expertise. Unfortunately, hiring experienced Data Scientists is extremely difficult and expensive, and this problem is only going to get worse as demand is expected to increase by over 40% in the next 5 years.
Spectra Analytics helps companies overcome the skills gap by providing access to their world-class team of PhD Data Scientists and proprietary AI technology. This reduces the execution risk for clients by reducing the cost, time to market, and failure rate.
We work across a broad range of industries from healthcare and defence to finance. Users of our technology include the NHS, UNICEF, British Army, US Marine Corps and many more. We have also provided Machine Learning Training on behalf of Google and GFT, and to professionals from some of the world’s leading companies such as Goldman Sachs, HSBC, KPMG, L&G….
This includes database management, data cleaning and enrichment from public and private sources (where possible) including social media
Data Science & AI
Providing business insights through mathematical and statistical modelling and machine learning.
Develop cutting-edge research for academia and business
Advisory & Training
Provide consultancy services and training for businesses on data analytics
Spectra work on fixed term projects and on a consultancy basis. Please contact us to see how we can help.
Case Study - Analytics Dashboards
The hospitality industry produces large amounts of data on people's travel and interests. This is particulalry, true of Online Travel Agents such as Expedia and Booking.com who track hotel and flight prices in real time. This data is helping consumers find better accomdation at better prices but it is also helping hotels connect with their target customers and monitor their competition.
We worked closely with Bloc, a small upscale travel hotel chain, to try to make sense of all their data by developing an Analytics Dashboard. The system monitors and analyses business metrics in real time and improves efficiency and productivity by automating report generation.
The system incorporates machine learning to analyse data from a wide variety of sources - such as the property management system, online travel agents, airports, local events, online reviews, Google Analytics, Google Adwords and weather - to forecast demand; predictive analytics. It then uses this information to optimise room pricing to maximise revenues; presecriptive analytics.
Case Study - Robotic Process Automation
The 4th Indutrial Revolution is ushering in a new era of automation which is impacting every aspect of business. This is a huge challenge for companies as they look to not only change their digital infrastruture but also change their company culture. Companies must become data led not just using data to support their decisions.
We worked with S6 - the UK’s largest network of FA-affiliated 5 & 6-a-side football leagues with over 30k members - to implement a large scale digital transformation programme.
Spectra developed a web app to automate leagues and team management and improve finance reconcilliation. The system also generates real time KPI’s to monitor live business performance. We also integrated marketing and customer interactions seamlessly with social media.
Case Study - Text / Document Analysis
Primary care is at breaking point as chronic underfunding, increasing demand - more patients, with longer term conditions – and a staffing crisis combine to create a perfect storm.
There are over 340m consultations per year with 26% (88m) of these potentially avoidable; costing the NHS >£1bn per year.
This led Spectra to develop PATCHS (Patient Automated Triage & Clinical Hub Scheduling), an AI-based triage system. The system optimises GP workload by managing patient demand and scheduling appointments. The system analyses patient symptoms, their medical histories and other external data to assess the seriousness of their condition and then recommends the optimal triage decision to the GP.
To generate it's triage decision PATCHS uses natural language processing to analyse patient symptoms and the Electronic Health Record.
This projected is funded by InnovateUK and being conducted with the University of Manchester
Case Study - Image / Video Analysis
Transport safety has improved significantly in recent years but there is still a long way to go. This can be seen through the UK transport statistics:
- 2,000+ fatal or serious road incidents in Greater London (5 years to 2015)
- 1,700 near-miss incidents, 66 collisions at level crossings (5 years to 2016)
- Approximately 7,000 platform-edge incidents (5 years to 2017)
Spectra Analytics have developed Deep-i, an Artificial Intelligence based motion tracking technology, for real-time safety monitoring.
Deep-i integrates with existing CCTV systems to monitor traffic flows.
- Generates alerts when there are dangers present, such as cars on closed level crossings or vulnerable users on station platforms, allowing users to take pre-emptive action
- Provides accurate statistics on the safety of traffic junctions and roads, by analyzing collisions and near-miss collisions, to inform transport authorities about potential risks and inform road safety investment
- Analyses road usage patterns such as traffic counts and user types
Case Study - Regulatory Reporting
Regulatory changes are making significant changes in the way in which financial institutions function. It is hoped that this will lead to greater transparency, improved consumer choice and increased stability. Unfortunately, these requirements have created a huge burden on financial institutions as they attempt to modify their business models to cope with the new regulatory environment.
Spectra worked closely with the financial brokerage firm XBZ to automate their processes to comply with MiFID II regulatory reporting requirements. This entailed integrating and normalising trade data from multiple sources and generating tailored reports for regulatory authorities.
Case Study - Market Surveillance
The financial industry is under heavy pressure from regulatory authorities to crack down on market abuse. In the UK alone, the financial regulator, the FCA, has imposed fines of over £225m for market abuse and £1.39bn for lack of governance and controls since 2013. Total fines for market manipulation globally in 2015 were nearly $9bn. This pressure combined with MiFIDII having been rolled out earlier in the year means surveillance is going to be a major focus for financial institutions.
The current surveillance market is highly fragmented with vendors each focusing on niche areas rather than holistic responses that are required. Even within these solutions the vast majority are first-generation rules-based technologies which are inflexible and highly prone to False Positives. These were the main challenges identified by PWC in their Market Abuse Survey 2016
To meet this challenge, Spectra have developed the MASER (Market Abuse Surveillance and Evidence Reporting). MASER is a next-generation trade surveillance system. MASER is a first line of defence surveillance tool designed to protect against market abuse and rapidly identify anomalies e.g. rogue traders. It utilises cutting-edge machine learning technology to identify illegal trading and market manipulation. Its configurable Trade Scenario Platform allows users to quickly add and test new scenarios in a robust and statistically sound approach.
MASER will become the first fully holistic surveillance tool, incorporating Electronic and Voice Communications Surveillance and Trader Performance Surveillance.
Case Study - Survey Analysis
Spectra worked with the Liverpool School of Tropical Medicine on behalf of Unicef to develop a statistical tool for public health teams to design Lot Quality Assurance Sampling surveys. LQAS is a survey design which uses stratified sampling to label regions as having either ‘acceptable’ or ‘unacceptable’ levels of an indicator. They are cheaper to perform than a traditional cluster surveys and regions can be combined to give point estimates. This work was then extend to Multiple Category LQAS and Large Country LQAS. These tools are available below:
Case Study - Spatial Analysis
Transport authorites spend a lot of time trying to improve accessibility but without good quality data this can be a big challenge. Spectra developed new analytics tools to study accessibility on the London transport network for mobility-impaired users. The aim was to identify 'mobility black spots' by calculating the time differentials between TfL recommended journey times and those of mobility impaired users. This information could then be raised to the relevant transport authorities. This was done by analysing the GPS data of mobile phones of mobility-impaired volunteers.
The project was funded by a European Commission Grant in association with Organicity