Our tone is light, the rest is not
While we keep the tone of the below examples playful and simple, each use-case is based on real-world situations and delivers measureable efficiency gains and/or sustainable growth. Contact us at info@sense6.ai to learn more about the underlying business case and deep-learning solutions.
Use-cases for Myriad
Use-case #1: automate manual processes
John's company receives many financial statements from its commercial customers. These arrive as raw PDFs with varying quality.
John doesn't like extracting KPIs from each statement: it takes time, it's redundant and error-prone copy-pasting, it doesn't utilize John's full potential.
Myriad automatically reads the PDFs and extracts the KPIs, creating a consolidated database in the process. John has some easy validation work and more time for value-add activities.
Use-case #2: prioritize tasks
Alice's team receives hundreds of email requests each day. These requests have varying importance, complexity and urgency.
Alice's team spends a great deal of time sorting through emails, and determining the most approporiate person to address each request to.
Myriad prioritizes the incoming emails and allocates them to the most suitable team member. If requests are simple, Myriad can even propose automated responses.
Use-cases for Deep Sense
Use-case #1: retain valuable customers
Over the past years Mary's company has been hemorrhaging its most valuable and loyal customers.
Mary's company is forced to increase prices on the fewer remaining customers, which leads to further departures and lower profitability.
Deep Sense identifies customer retention patterns in the company's historic data. Mary's company tackles the root cause of the problem and breaks the vicious circle.
Use-case #2: predict claims performance
Daniel is part of the commercial underwriting team of an insurance company. He is responsible for estimating the claims that different SMEs will have in the future over a 3-year horizon.
Daniel uses a number of metrics - industry, company size, geographic footprint - and a complex model to make his predictions. He wonders whether more accurate predictions are possible.
Deep Sense uses all metrics available in the historic customer data to train itself and predicts future claims performance. This new model complements Daniel's pre-existing approach and performs better than traditional algorithms.
Use-case #1: automate the customer journey
Bill's company launches a new generation of pay-as-you-go services for SMEs, these require a lot of upfront information.
The new SME customers are unwilling to fill out lengthy forms and therefore aren't purchasing the new pay-as-you-go services.
Cloud Link pulls up-to-date SME metrics from the cloud, reducing the amount of information that new customers need to provide. The launch gathers momentum.
Use-case #2: know who you are dealing with
Claire is head of fraud detection at a bank. Each day her team is responsible for checking thousands of transactions.
Claire is overwhelmed by the high number of transactions. Her team can only check a handful, mostly resorting to a few Google queries.
Cloud Link uses multiple official data sources, for example government debt enforcement reports, to increase transparency and raise warning flags on select transactions.
Use-cases for IOT
Use-case #1: predictive maintenance
Vanessa's company has deployed hundreds of machines across multiple customers and locations. Maintenance is part of daily business and has a significant impact on costs and customer satisfaction.
Vanessa wants to stop being reactive and reach her customers efficiently before her machines break-down. Unfortunately the sensors of her machines are disconnected.
Our configured IOT modem-routers are deployed at each location, create a secured connection and regularly query local sensors. Alarms can be triggered ahead of break-downs, and Vanessa's engineers can log-in to any location and trouble-shoot remotely.
Use-cases for Augmented Reality
Use-case #1: risk engineering
Coming soon
We think that we can help you
Most companies we know are impacted by at least one of the the above use-cases or derivation thereof.

However a project doesn't always make sense: (i) "size of the pain" and (ii) "ease of implementation" vary case-by-case and are the two main drivers for a decision to proceed. The good news is that they are fast to assess: usually within two 1-hour meetings.

Please contact us at info@sense6.ai, especially if you have a specific use-case that you want us to take a look at.
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