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Lufthansa

Elevated Lufthansa Airlines offerings, With their comprehensive Digital transformation Journey. In consideration to the Guidelines laid by DGHCA, FAA, EASA.

3 Months

Industry: Aviation

Technical Stack Used: Machine Learning, NER, Deep Learning, Transformer Models, Python

Service: Digital Transformation

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Project Details

lufthansa

The goal of the project is to assist Lufthansa Airlines in their complete digital transformation journey. This involves overhauling their existing solution to align with the latest technology stack and design practices, ultimately empowering them with an AI-driven solution.


Problem

  • Lufthansa Airlines had an holistic DRM solution in place, Which helped them in managing the records of the assets traded in between the Lessee and the Lessor.
  • The existing DRM solution faced several challenges, including an outdated technology stack, exorbitant cloud expenses, elevated operational costs, and inefficiencies.
  • Each lessor in our context the Airlines, needed to maintain the record of the craft maintenance during the lease period . Which needed to be presented to the relevant regulatory body.
  • Count of records such as routine maintenance, inspections, repairs, component replacements, compliance documentation, Job Cards were around thousand for a single aircraft,. Impacting the storage cost, Audit cost and efforts for ensuring the correct documents are getting mapped to the right category.

Our Approach

  • Starting off for the digital transformation Journey, We actively conducted a primary research of each Personna. Did a through tech audit to figure out the improvement avenues in terms of Technology Advancement and controlling cloud expenses.
  • Entire digital strategy was designed. Outcome of the same was a refined technical debt, Considering the easy wins and maximum impacts on the top priority.
  • On functional aspect, Designed the Product and Design backlog as per the current customer needs and latest design trends. AI enabled solution were parked in considering quick audit and less manual intervention.
  • Post conducting the infrastructure audit, A strategy was designed in order to reduce the cloud expenditure and curtail the proportional month on month increment in cloud cost.
  • Entire M&E system was revamped, Where engineers on ground can easily update the relevant records against the maintenance activities that have been taken care off.
  • An AI driven solution to enable the bunching and categorization of the documents uploaded by the M&E staff
Solution for lufthansa

Benefits

  • Were able to derive the plan for improving the customer onboarding, narrowing down the time to onboarding of the customer from 4-5 months initially to a month.
  • Our infrastructure audit helped us to chalk out the plan for reducing the infrastructure and cloud cost to nearly around 25%.
  • Using the audit, we were able to determine the technical, functional and design tasks that were easy to achieve and can make a big impact in terms of UX.

Meet the Experts Behind This Project

Every successful software transformation is powered by experienced engineers, architects, designers, and AI specialists. Connect with the experts who have delivered scalable digital solutions across healthcare, fintech, retail, manufacturing, education, and other enterprise industries.

GK

G. Kaur

Senior Data Scientist | 4 Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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Python
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PyTorch
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MLOps
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Forecasting
RS

R. Sharma

Senior Solution Architect | 4+ Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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AWS
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Cloud Architecture
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Microservices
PM

P. Mehta

Lead AI & Data Engineer | 2+ Years of Experience
4.5/5 | (4.5/5 by 100+ clients)

Specialises in:
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AWS
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Generative AI
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ML
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Python
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