AIMLEAP - Outsource Bigdata

BACKGROUND
A leading realty aggregator company has been working with a US-based
start-up company for their data solutions for about three years. The
aggregator was in search of a new provider for their data solutions to
save cost and increase efficiency and one of our clients referred the
aggregator to AIMLEAP Outsource Big Data Automation.

APPROACH TO SOLUTION
AIMLEAP - Outsource Big Data built custom BOTS for web data scraping
from 35 web sources in the US and Canada. Automated the end-to-end
process for the real estate aggregator company to synchronizes and
harmonize its development and support processes towards the pursuit
of operational, quality, and governance excellence. The automated data
processes helped the company to meet its operational scalability, time
to market, and increased customer experience.

HIGHLIGHTS
▪ Saved $60000 per year
▪ Reduced end-to-end data processing time by about 60%
▪ Set a process to scale up operations by 80%

BACKGROUND
A leading energy product data service provider company has been
working with AIMLEAP for over 7 years in different data collection, data
enrichment, and data enhancement projects. AIMLEAP was working
more on their back-end data processing part.
Their existing vendor for automation and further analytics solution was
slightly expensive. Hence, energy data services company with a broad
vision for automation and analytics turns to AIMLEAP to reduce cost &
increase efficiency.

APPROACH TO SOLUTION
AIMLEAP - Outsource Big Data developed a proof-of-concept for
automation based on Robotic Process Automation. POC was well
accepted and automation implemented in the end-to-end project. Also,
AIMLEAP deployed analytics professionals to replace the current
analytics – model monitoring and support activity.

HIGHLIGHTS
▪ Saved $70000 per year
▪ Reduced end-to-end data processing time by 40%
▪ Increased ability to scale up the process for market expansion by 60%

BACKGROUND
A major real estate service provider company wanted to streamline its
inefficient real estate agent-servicing process. The existing process
required multiple data analysts, with help from the in-house IT support
team, to manually collect data from 20+ different data sources. Data
received from 20+ sources was the indifferent quality, format and had
multiple other challenges. The internal IT support system was not robust and
it further slowed the entire process.
Also, as it was a manual process - analysts were able to process only a
a limited number of records, based on priority, creating backlog and
struggled to serve their existing and new set of customers. The company
approached AIMLEAP – Outsource Big Data help in streamlining its
processes and providing end-to-end solutions.

APPROACH TO SOLUTION
We quickly developed a proof-of-concept for suggested a solution
based on Robotic Process Automation to replace the company’s
manual processes for collecting data from 20+ sources integrated to a
base IT support system.

HIGHLIGHTS
▪ Saved $40000 per year.
▪ Increased data handling capacity by 60%
▪ Average data processing time reduced by 85%
▪ Increased ability to access data in real-time

BACKGROUND
An Equipment Leasing & Financing Company in Canada approached AIMLEAP for their end-to-end web data scraping, cleansing, formatting, and related IT solutions. The Company was in search of a competitive provider who has capability in automation and IT side to save cost and increase efficiency.

APPROACH TO SOLUTION
AIMLEAP - Outsource Big Data Team developed web data scraping automation system, data warehousing system, and Google map-based dashboarding with the intuitive user interface. Leveraging multiple components to process this data using UI Path, Google BigQuery, Google CloudBucket, Google Data Studio, Google Map API, and an HTML5 website to display results. The semi-automated processes helped the company to meet its operational scalability, time to market, and increased customer experience.

HIGHLIGHTS
▪ Automation saved overall cost about $60000 per year
▪ Reduced data processing time by about 60%
▪ Increased service levels improve customer experience & revenue

BACKGROUND
• A leading management consulting company based out of the USA wanted to collect US County-level legal cases data every month.
• It was manually mining data from multiple court websites and was looking for an optimized solution.
• For mining a single case, the customer had to visit multiple web pages and tabs. Approximately nine tabs for each case and each tab had its unique complexities and formats.
• Expected output was - a ready-to-upload excel file that supports creating their in-house database.

APPROACH TO SOLUTION
• AIMLEAP - Outsource Big Data Team built custom BOTS for web data scraping from multiple sources
• Only US IP (Internet Protocol) was able to load case data from the web source, hence we deployed US IP to access the data
• Scheduled monthly scraping process to scrap new cases added to the court websites
• Custom built web crawler was able to mine the legal case data in almost close to the template format provided by the customer and this reduced manual intervention substantially

HIGHLIGHTS
• Above 98% data quality consistently
• An approximate 75% cost saving
• Quick turnaround

BACKGROUND
• Customer was looking for an integrated data solution by building a database of 1.2 million - laboratory equipment data from online and offline sources
• The multiple sources data did not have a uniform structure
• The lab products having a different format with 1.2 million rows and 900+ columns
• Customer wanted all products and related images to be downloaded and zipped into a single file, along with the link of the image in the output .csv file
• Customer was looking for an optimized solution for data collection

APPROACH TO SOLUTION
• AIMLEAP - Outsource Big Data Team developed web data scraping automation system and connected to internal data sources
• Custom web crawler was able to mine desired data points – instead of all dump data -- in the desired template by the customer. This reduced manual intervention substantially
• The semi-automated processes helped the company to increase its operational scalability, time to market, and increased customer experience.

HIGHLIGHTS
▪ Automation saved overall about $25000 per year
▪ About 50% efficiency gains
▪ Scalable and robust solution

BACKGROUND
A leading management consulting company based out of US wanted to
develop an employee management application which includes:
- Employee data management
- Timesheet management
- Salary processing
- Invoice generation
Also, the consulting company was looking for a cost-effective enhancement,
maintenance, administration, support for application on a regular basis.

APPROACH TO SOLUTION

AIMLEAP - Digital IT Team built a web application which manages

• Automated template-driven employee data management

• Time Sheet: One-click solution for entering daily timesheet

• Salary data management: Automated salary data calculation and processing • Invoice generation: Semi-automated invoice generation

HIGHLIGHTS

• Cost-saving – annual FTE reduction ~ 3

• Increased process efficiency 60%

•Increased employee engagement

BACKGROUND
An AI solution focussed start-up company based out of the UK wanted to develop an employee management application that includes:

The customer wanted 250 million specious images to be mined.

The customer had a list of 2.5 Million species scientific and generic names.

The customer was particular to collect 2.5 million species all in 10 HD (High Definition) images and sources suggested were Flickr/Instagram/Google.

The customer was looking for an optimized solution for image data collection and streamline the end-to-end process for the AI solution.

Also, the start-up was looking for a cost-effective solution that can further periodically add to the AI system.

APPROACH TO SOLUTION
AIMLEAP - Outsource Bigdata Team automated the image sourcing process by building

A custom set of web crawlers built including paid Google API to mine image data.

The crawler that was able to mine required image data with minimal manual intervention.

The team performed semi-automated image data validation and
ensured that images are of expected quality.

Also, an automated process established to feed the final set of qualified images to push to the customer database at a regular interval

HIGHLIGHTS
90 % cost saving
Above 95% quality assured
Quick Turn Around – delivered 250 million images in 60businesd days

BACKGROUND
▪ A US-based fintech start-up wanted to build a big data analytics
solution; and was looking for a suitable partner.
▪ Start-up was looking for an optimized solution to source 10-year
financial data for 500 companies
▪ The data expected in a custom grid format to feed the analytics
engine

AIMLEAP APPROACH TO SOLUTION
▪ AIMLEAP -  Outsourcebigdata  Automation Team leveraged AI-driven data solution to
build a semi-automated process to convert source data
▪ AI solution was trained to identify data points that needed
manual intervention
▪ The AI solution was able to source and convert financial data with
minimal manual intervention
▪ Automated data validation process assured that all data points are
of expected quality
▪ Also, an automated process established to feed the final set of
data to push to customer database on a regular interval

HIGHLIGHTS
▪ 60% cost saving
▪ 99% data quality
▪ Quick turnaround helped faster Go-To-Market