Innovation Services

Robotic Process Automation

Artificial Intelligence Platform enables you to develop Digital Virtual Agents, Chatbots, Predictive agents and cognitive process automation.

Natural Language Processing

Customer Analytics Solutions for understanding customer behavior, enabling product recommendations and Predictive Analytics.

Cognitive Customer Analytics

IT Operations Analytics solutions for operations resource planning and making better decisions about your IT environment.

Enterprise Operational Analytics

Emin Cyber Labs mission is to help customers achieve their business objectives by providing innovative, best-in-class consulting, IT solutions and services and to make it a joy for all stakeholders to work with us.

Solutions for Building Artificial Intelligence Customized and Scalable AI Applications
Empowering AI-Based offerings for deriving actionable insights from Images, Videos and increasing business efficiency with custom Image and Video Analytics Solutions. Using our knowledge of industry-specific business processes and challenges, we tailor our artificial intelligence solutions to your particular needs. Whether you want to automate back-office operations, boost customer experience, improve security, or launch a truly innovative software product, our AI specialists are up for the challenge. Our AI specialists help Enterprises achieve high-quality, high-accuracy capabilities that enable developing cost-effective AI-Driven Products and Solutions.

Driving and Scaling enterprise AI for business value: Assisting Enterprises in building AI Strategy to optimize existing business and distinguish places where AI can generate the most significant value.

Defining Business Outcome and Metrics: Assisting businesses to improve workforce productivity, decrease operational costs, and facilitate quicker insights.

ModelOps and Explainability AI: With Edge AI-Based Solutions, Enterprises can facilitate Real-Time decision making, leverage advanced edge analytics abilities, and enhance Data Security.

Enabling Data-Centric Approach: Intelligent Video Analytics solutions empower organizations to build Image Classification abilities and Advanced Analytics Capabilities.

Scaling AI based capabilities for Enterprises: AI-Driven Transformation roadmap requires Businesses to Strategize for Scale, incorporate Ethical AI principles, and develop a robust infrastructure. Revolutong business processes and development of products with Artificial Intelligence based Solution offerings.

Learn

Start by understanding what RPA can and cannot do. RPA technology helps your organization run more efficiently by taking repetitive manual tasks and handing them over to software robots.

Identify

Hearing about the benefits of RPA will make you want to automate everything. But to be successful, you need to start small.

Select

Rank your wish list by considering the time saved, frequency, criticality, and effort it would take to automate, and select the process that checks the most boxes.

Pilot

There are lots of RPA solutions out there, but they’re not all created equal. This is a great time to try different RPA solution. And try Pilot solution for initial use case.

Measure

It should be easy to measure the results of your pilot use case. Take a look back at how things went and document what went well, what could’ve been better, and any other lessons learned.

Expand

Expand to next use case and repeat pilot, measure and expand steps. The steps of the RPA journey don’t have to end as there’s always processes that can be streamlined through RPA.

Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions. In practice, you know you’ve got modern business intelligence when you have a comprehensive view of your organization’s data and use that data to drive change, eliminate inefficiencies, and quickly adapt to market or supply changes.

Much more than a specific “thing,” business intelligence is rather an umbrella term that covers the processes and methods of collecting, storing, and analyzing data from business operations or activities to optimize performance. All of these things come together to create a comprehensive view of a business to help people make better, actionable decisions. Over the past few years, business intelligence has evolved to include more processes and activities to help improve performance. These processes include:

Data mining: Using databases, statistics and machine learning to uncover trends in large datasets.
Reporting: Sharing data analysis to stakeholders so they can draw conclusions and make decisions.
Performance metrics and benchmarking: Comparing current performance data to historical data to track performance against goals, typically using customized dashboards.
Descriptive analytics: Using preliminary data analysis to find out what happened.
Querying: Asking the data specific questions, BI pulling the answers from the datasets.
Statistical analysis: Taking the results from descriptive analytics and further exploring the data using statistics such as how this trend happened and why.
Data visualization: Turning data analysis into visual representations such as charts, graphs, and histograms to more easily consume data.
Visual analysis: Exploring data through visual storytelling to communicate insights on the fly and stay in the flow of analysis.
Data preparation: Compiling multiple data sources, identifying the dimensions and measurements, preparing it for data analysis.

Business intelligence is continually evolving according to business needs and technology, so each year, we identify current trends to keep users up-to-date on innovations. Realize that artificial intelligence and machine learning will continue to grow, and businesses can integrate the insights from AI into a broader BI strategy. As companies strive to be more data-driven, efforts to share data, and collaborate will increase. We follow up-to-date BI solutions to provide best BI services to our cilents.

What is robotic process automation?

Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that emulate humans actions interacting with digital systems and software. Just like people, software robots can do things like understand what’s on a screen, complete the right keystrokes, navigate systems, identify and extract data, and perform a wide range of defined actions. But software robots can do it faster and more consistently than people, without the need to get up and stretch or take a coffee break.

What are the business benefits of RPA?
Robotic process automation streamlines workflows, which makes organizations more profitable, flexible, and responsive. It also increases employee satisfaction, engagement, and productivity by removing mundane tasks from their workdays.

RPA is noninvasive and can be rapidly implemented to accelerate digital transformation. And it’s ideal for automating workflows that involve legacy systems that lack APIs, virtual desktop infrastructures (VDIs), or database access.

Why is RPA transformative – Innovative?
Software robots—instead of people—do repetitive and lower-value work, like logging into applications and systems, moving files and folders, extracting, copying, and inserting data, filling in forms, and completing routine analyses and reports. Advanced robots can even perform cognitive processes, like interpreting text, engaging in chats and conversations, understanding unstructured data, and applying advanced machine learning models to make complex decisions.

When robots do these types of repetitive, high-volume tasks, humans are freed to focus on the things they do best and enjoy more: innovating, collaborating, creating, and interacting with customers. Enterprises get a boost too: higher productivity, efficiency, and resilience. It’s no wonder that RPA is rewriting the story of work.

Is RPA the same as artificial intelligence (AI)?
RPA is not AI; AI is not RPA. But the combination of RPA and AI unlocks massive new possibilities for enterprises everywhere. For one thing, RPA technology now makes it possible to insert advanced AI skills in the form of machine learning models, natural language processing (NLP), character and image recognition, and more into RPA robots. Giving robots these AI skills dramatically expands their ability to handle cognitive processes that require things like:

Understanding documents including semi-structured or unstructured data
Visualizing screens (including virtual desktops)
Comprehending speech and carrying on conversations and chats

AI is also making it possible to scientifically discover a complete range of automation opportunities and build a robust automation pipeline through RPA applications like process mining.

And at a time when companies need to accelerate their integration of AI into front-line activities and decisions, many are finding that RPA can serve as AI’s ‘last-mile’ delivery system. Robots can be configured to apply machine learning models to automated decision-making processes and analyses, bringing machine intelligence deep into day-to-day operations.