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We help you set up Data Analytics Solutions customized for your business to uncover hidden opportunities and ensure better decision making for the future. Our comprehensive range of Data Analytics Services help categorize, contextualize, scope, and derive actionable data insights to address business challenges and generate value

We build a data and analytics strategy based on our subject matter expertise to deliver services that suit your enterprise requirements

Over years of successful Business Intelligence delivery, we have helped clients extract maximum value from their historical data with our technology-agnostic approach and Business Intelligence framework. This has helped our clients support their business decisions and automate repetitive/routine activities like daily reports, status emails, etc



We are technology leaders in the market of personalized mobile application development that gain popularity for developing the industry-best mobile solutions for B2B, B2C & B2E business environments. We offer hassle-free mobile app development services while adhering to strict standards and protocols.

We help choose the right Cloud Native environment for the software, design a highly performant and scalable data architecture to meet client needs, design a cross-platform and aesthetically pleasing user interface, develop microservices to ensure a highly performant back-end to the application and provide automated testing throughout to help speed up time to market.

Based on our extensive experience developing SaaS solutions for our customers we have developed a suite of accelerators to jumpstart application development which means the solutions we develop will be built on tested methodologies and have a shorter development lifecycle. We also build custom solutions tailored to client requirements.



We Use AI applications within marketing. We define which AI applications to use first based on the value these can bring. Our in house applications of AI in marketing are:

  • Data Insights – AI can be used as a tool to provide data insights, specifically for marketing teams who don’t have access to data engineers. For example, AI models can identify patterns in customer data and autonomously cluster customers based on those patterns. AI can also support result analysis by helping discover the impact campaigns had on different KPIs by powering analytic models such as marketing mix modeling and multi-touch attribution.

  • Personalization – A common use case of AI in marketing is for personalization. Due to their scale and speed, AI models are particularly helpful when needing to identify customer preferences and personalize content in realtime. Common use cases for AI in personalization include models for product recommendations, dynamic websites, self-optimizing campaigns (where the model determines the best treatment from a multivariate test for each individual customer) and personalized messaging via chatbots.

  • Campaign Recommendations – AI can also be used to recommend content to marketers as they build their campaigns. Use cases around this application focus on tone of voice recommendations and reviews and image recommendations.

  • Scheduling – Viewed as a subset of Campaign Recommendations, scheduling is one of the most common uses of AI in marketing. With each customer preferring to receive communications at their own time, and based on each individual’s open and click patterns, send time optimization algorithms have become a popular capability in marketing automation software.

  • Programmatic Advertising – For marketers advertising digitally, leveraging AI for programmatic advertising provides great benefits. By analyzing data in realtime, AI models can help predict results of campaigns for different audiences, adjust bidding strategies to maximize ROI and match content to audiences to increase relevancy.

  • Next-Best-Action Decisioning – The most advanced form of AI in marketing is its application for next-best-action decisioning. This refers to the use of AI to determine which campaign is best for each individual customer, instead of abiding to marketer determined automations. In this setup, marketers define the campaigns and segments (which as said above can also be AI-aided), and the algorithm determines which to deliver to each customer, from all the available possibilities.


Block Chain

Cyber Security

Digital Code 13 provides high-availability architecture to allow for seamless scaling and a failure resilient infrastructure with 99.9% uptime out of the box. Nodes are fault-tolerant, high-traffic nodes which include redundancies to handle high traffic and ensure a node failure does not take the network down.

We puts security of our products and offerings first. By abiding by best in class security practices and compliance we ensure the utmost adherents to industry standards to give our customers piece of mind in their node operations.

Threat Notification Isn’t the Solution – It’s a Starting Point

Other managed detection and response (MDR) services simply notify you of attacks or suspicious events. Then it’s up to you to manage things from there.

With Sophos MTR, your organization is backed by an elite team of threat hunters and response experts who take targeted actions on your behalf to neutralize even the most sophisticated threats.



Complete Control

and Transparency

We do the work, but you own the decisions. This means you control how and when potential incidents are escalated, what response actions (if any) you want us to take, and who should be included in communications. Weekly and monthly reports let you know what is happening in your environment and what steps have been taken to keep you safe.


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