Why Choose Zillionica?
The place to discuss startup problems and solutions. Zillionica has been providing comprehensive Information Technology (IT) solutions and support for businesses of all sizes and industries since few years.
Startup Services
We understand the challenges that startups and entrepreneurs face, and we are very flexible in our business models in working with startups adjusting to their special needs.
Financial services
The right financial services technology can help a financial service company generate new opportunities, maximize current relationships, and streamline day-to-day operations.
Devops
DevOps aims to collaborate and connect the bridge between the Development team (Dev) and the Operation team (Ops).
DevOps
Well, DevOps is neither any tool, technology, or platform. It is rather a culture or a set of principles and practices that Businesses adopt in their Software Development environment. DevOps aims to collaborate and connect the bridge between the Development team (Dev) and the Operation team (Ops). It can be said to be an extension of Agile, which incorporates other practices such as Continuous Integration, Continuous Delivery, and more. So DevOps ultimately helps to shorten the development life cycle. And as a result, allow companies to accelerate the delivery of Software Products. Because of the incredible value that DevOps brings into a Business, it is quickly gaining an incredible amount of attention all across the Globe.
DevOps Automation
Automation is one of the ultimate needs and key principles of DevOps. Besides, automation of Infrastructure set up and configurations along with Software deployments is what makes DevOps a global trend in the IT space.
DevOps Assessment
As part of Our DevOps Services, We provide complete assessment and strategy planning offerings
DevOps CI/CD Pipeline
Continuous Integration(CI) and Continuous Delivery are the two pillars of a thriving DevOps environment.
DevOps CI/CD Pipeline
Continuous Integration(CI) and Continuous Delivery are the two pillars of a thriving DevOps environment. CI/CD Pipeline is the process or workflow constituting a set of different tasks and stages through which we help deliver a production-ready Software product. In DevOps, the entire CI/CD Pipeline is automated, and this is what we are responsible for. We help create, automate, and simplify the different stages or the entire Pipeline. Our team of talented individuals is passionate about automation, and hence, they can employ the right set of tools for creating and maintaining CI/CD Pipelines. We implement different tools for different stages and Practices ( head down to the below section to know what tools we use) which includes:
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Our DevOps engineers put into action specific tools that allow developers to continually merge code changes and update them to a shared (central) repository. And once codes are committed, it triggers the automated build and test systems. |
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We adopt a range of tools using which one can automate the entire pipeline, and any code change s automatically pushed to production. So this results in multiple production deployments in one day. |
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DevOps on the Cloud
DevOps is all about improving the software development process. While Cloud Computing is a technology service.
DevOps configuration management
With Our configuration management services, We can help manage your code, automate, and monitor your platforms and make your server as well as your facilities ready for your Customers.
DevOps Infrastructure Management
Infrastructure Management is an essential aspect for any organization making the transition to a DevOps culture.
Startup company Services
We understand the challenges that startups and entrepreneurs face, and we are very flexible in our business models in working with startups adjusting to their special needs. Our extensive expertise in transforming your ideas into great products includes full-cycle application development services including:
- Assessment, roadmap and software architecture design
- Rapid prototyping and Proof-Of-Concept development services
- MVP design and development
- Front-End, UI and UX services
- Mobile application development
- Cloud engineering and optimization
- DevOps services
- Analytics and Big Data Solutions
- AI/Machine Learning implementation
- Software quality assurance, testing and test automation
- 24x7 Maintenance and Support
Machine Learning
What we Offer in Machine
Learning as service?
Machine learning has become a buzzword in recent years, with companies like Google, Facebook, and Amazon all embracing the technology. The idea is to learn from data to provide services that are better than what humans alone can offer. These are AWS Machine Learning and Microsoft Azure Machine Learning Studio. Both of these technologies have the potential to transform our organization but choosing the right one can make all the difference. To a hammer, everything looks like a nail, but to get the most out of these platforms, engineers must appreciate the wide variety of tools offered by each. Using Machine Learning as a Service means we don’t have to worry about managing infrastructure, setting up servers, installing software, and so on. We just connect the relevant training data, select the column to predict, and let the service do its magic.
What is it and how can it help your businesses?
Machine learning is all the rage right now. It claims to
revolutionize the way
computers will work.
Machine learning is set to change the way we do business. Machine learning combines mathematics,
statistics, and artificial intelligence into a new discipline of study.
Big data and faster computing power are opening up new capabilities for this technology that seemed
impossible only a decade ago.
Data Analytics
Data analysis services allow businesses to get their data collected, processed and presented to them in the form of actionable insights while avoiding investments in the development and administration of an analytics solution.
Descriptive
In order to analyze data, companies first need to collect and aggregate raw data from various sources and convert it into a common format for analysis. Then they’re ready to analyze the data. Many companies use data intelligence, or a group of methods and tools used to collect and analyze data then form conclusions and action plans based on the findings. Others use spreadsheet formulas to apply basic descriptive analytics to the aggregated data, generating KPIs and other statistics that are then included in reports. Integrated ERP suites make descriptive analytics much easier because they can store all the organization’s business data in a single database.
Dignostic
In order to analyze data, companies first need to collect and aggregate raw data from various sources and convert it into a common format for analysis. Then they’re ready to analyze the data. Many companies use data intelligence, or a group of methods and tools used to collect and analyze data then form conclusions and action plans based on the findings. Others use spreadsheet formulas to apply basic descriptive analytics to the aggregated data, generating KPIs and other statistics that are then included in reports. Integrated ERP suites make descriptive analytics much easier because they can store all the organization’s business data in a single database.
Predictive
In order to analyze data, companies first need to collect and aggregate raw data from various sources and convert it into a common format for analysis. Then they’re ready to analyze the data. Many companies use data intelligence, or a group of methods and tools used to collect and analyze data then form conclusions and action plans based on the findings. Others use spreadsheet formulas to apply basic descriptive analytics to the aggregated data, generating KPIs and other statistics that are then included in reports. Integrated ERP suites make descriptive analytics much easier because they can store all the organization’s business data in a single database.
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Prescriptive
Due to the sheer amount of data now available to companies, it’s easier than ever to leverage information collected to drive real business value. However, it can be tricky to identify the best way to analyze this data. Applying prescriptive analytics is one option that can assist your business in identifying data-driven strategic decisions and help you avoid the limitations of standard data analytics practices, including:
Financial Services
Automate Financial services to Drive Greater Efficiency, Compliance, and Productivity The right financial services technology can help a financial service company generate new opportunities, maximize current relationships, and streamline day-to-day operations. This guide will serve as a roadmap for your buying journey. In it, you’ll find: three functional areas of financial services software; common software features; leading solutions by category; industry trends and special considerations; and a detailed case study.
Accounts Payables & Receivables
Integrate ERP, CRM, and accounting systems to track all paid and unpaid invoices and use automated workflows to increase process efficiency and reduce the burden on staff. Efficiently manage the core business functions from accounting, purchasing, sales and customer relationships to reporting.
Budget & Revenue Forecasting
Get a better assessment of your company’s future trajectory and collaborate with key stakeholders to analyze data from multiple data sources for unified budget and revenue forecasts
Quote to Cash
Integrate your ERP, CRM, CPQ, and payment processing solutions to sync customer, contract, and pricing data. The app automates workflows for quote to order Q2O, CPQ, order to cash O2C, fulfillment, and more.
Invoice Processing
Simplify invoice management with an out-of-the-box app that connects to your CRM, ERP, & accounting systems. It captures invoice data from different documents & automates invoice processing workflows.
Provide a 360-degree customer view
One of your biggest assets is your customer data. To drive digital transformation, you need to promote standardization and improved context across customer data. Stardog helps you build a unified view of customer data resulting in improved data context and quality, enhanced analytical capabilities, and increased searchability and discoverability of customer data.