spaceport

Scale your business to the Cloud

Our Approach

From whiteboard sketches to creating detailed visual models, from designing the future infrastructure and data pipelines to deploying highly flexible and scalable environments, we provide the full range of Big Data SaaS solutions and highly-adjustable DevOps processes for startups and established corporations alike.

  • Learn

  • Manage

  • Analyze

  • Culture

  • Run

  • Code

  • Delivery

Harnessing

Tap into a huge goldmine of previously unused metadata your business already possesses. Grow your returns on advertising up 16x with our help!

Data Gathering

Use the modern technology to harness the richness of data generated by your business, customers and the rest of the market players to stay ahead of the competition!

Visualization

Benefit from visualized representation of the analysis of your data stores. Get clearly identifiable trends and anomalies within your data to maximize profits or mitigate the risks of fraud.

Analytics

Explore the wealth of analytical information to discover hidden patterns, anomalies, possible security breaches and much more, which allows gaining and empowering the competitive edge.

Infrastructure

Be prepared for the ever increasing volume and complexity of the Big Data processed by benefitting from top-notch cloud infrastructure we deploy.

Machine Learning / AI

Exploit the machine learning algorithms for delivering truly personalized user experience analyzing strategic data.

IoT

Ride the tide of interest for smart household systems and conquer new markets with your IoT solutions!

Blockchain

Ensure 100% security of distributed databases with the help of our blockchain-powered tools.

Cloud
architecture

Harness the power of Kubernetes to easily deploy your apps in Docker containers on public or on-prem private cloud

CI/CD

Utilize Continuous Integration and Continuous Delivery to the max, ensuring rapid software development and release within tight timeframes.

Automation

Use all benefits of automation by deploying infrastructure as a code. Free your developer team’s resources from routine tasks and allocate them to improve the business workflow.

Testing

Minimize the risks of bugs and downtime on release by introducing strenuous automated testing.

Security

Benefit from top-notch security solutions that ensure safe storage and processing of mission-critical information

Logging

Keep all the vital data at your fingertips due to convenient logging of all events and actions in the system to provide solid ground for decision-making.

Monitoring

Utilize real-time monitoring to ensure stability and predictability of all business processes, from client management to software deployment.

Alerting

Stay in touch with your business at all times with email, SMS, and other alerts to make sure any unexpected event is dealt with quickly and efficiently.

Our Cases

Natural Language Generation Engine(NLG)

One of the main problems the analytics department in corporate business faces is the sheer volume of incoming and outgoing data, meaning the analysts have to write LOTS of text (most of which is never read). This is particularly painful for writing monthly or quarterly reports, especially if they are intended to be actually useful. We came up with a solution that lowered the quantity of human errors by 58% and provided a 71% faster report writing.

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NLP Job board

There is another solution we built from scratch for a high-tech start-up — an innovative job board for Asian market. This job board must serve the healthcare and medical science industry and is oriented at top-tier researchers and scientists. There was a dual challenge — both the employers and the applicants cannot describe their skills precisely (either because they cannot lift the NDA or the project descriptions involve highly specific terminology).

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Financial Quantitative Analytics

We have developed a backbone of the Machine Learning platform for financial quantitative analytics. The core problem of existing manual analytics modelling methods is that they take a long time to build a model, while the data remains relevant only for 30 days or even less. Thus said, building a model should happen fast in order for it to remain relevant for long.

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Cloud is no rocket science. See for yourself.

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