Sparta is an enterprise software and machine learning platform that aims to help retail and distribution companies optimize their operations. It combines an ERP platform with built-in machine learning capabilities to automate processes, provide intelligent analytics, and deploy continuous learning models. The platform addresses common issues like inventory management, cash flow monitoring, and returns processing. It is offered as a SaaS product with pricing varying based on the number of users and package level. The founding team has experience working for large companies and developing software.

1. IwoRK Technologies llc
Pitch Deck

2. Presenting sparta!
The Enterprise Software
with a built-in ML platform
.
2
Fixing the Retail Industry with Automation and Machine Learning

3. Our Vision is backed by Numbers
3
• 76% of enterprises prioritize AI and Machine Learning (ML) over
other IT initiatives in 2021
• The global machine learning market size is expected to reach
$96.7B by 2025
• 83% of enterprises have increased their budget for AI and
machine learning year-over-year from 2019-2020
• By 2025, 50% of enterprises will have devised artificial
intelligence (AI) orchestration platforms to operationalize AI

4. $575,000,000,000
Overall Enterprise Application Software will expand to a
$575B market by 2025*
4
PRNewswire.com*
**
Market Potential
$23,000,000,000
AI/ML market size for retail markets by 2027**

5. Erp + ml = sparta
Sparta is a brute force backed by Machine
Learning for all levels of enterprises working
in retail and distribution.
5
The Setup

6. Sparta - BEST OF BOTH WORLDS, a new type of enterprise software
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ERP Platforms
- Oracle
- Sap
- Microsoft dynamics
Third party (rpa/ai-ml)
- Splunk
- Blue prism
- Uipath
Sparta

7. The Problems Today…
Enterprises in the retail market don’t leverage their data to the max
Impossible to convert data insights into meaningful patterns using Excel
Legacy applications are not automated with human error eroding the data
Most businesses are forced to buy and integrate 3rd
Party software
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8. A ML model deployment
platform
Sparta ML (SML) sorts all the data
in the system for ease of use
accordingly. Backed by Machine
Learning, SML lets you deploy
continuous models for multiple
iterations.
solutions
Intelligent Automation
Accomplish tasks by minimizing
human intervention using process
automation. Replenish stocks, close
accounts, clear up your AP and
more with minimum to no clicks.
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Robust Enterprise Software
Sparta Enterprise (SE) was
designed for the user. Experience a
B2C quality interface coupled with a
comprehensive list of integrated
modules.
Smart Analytics
Utilize dashboards and get clear
insight on what's going on inside
your organization. Enable your data
engineers to access structured data
sets.

9. Case study 1: Retail Industry Operations affected by Covid-19
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An enterprise software + ML platform can give companies an edge.
During the pandemic, retailers shifted towards BOPIS or Buy Online, Pick-up In Store. While deploying BOPIS,
companies claim that 45.6% of the time, issues stem from Logistics and Inventory Tracking.
✔ Gather stock movement data
(Sparta Enterprise or SE)
✔ Incorporate IoT sensors for
real-time data (SE)
✔ Detect inconsistent supplier quality
levels (Sparta ML or SML)
✔ Fix forecasting error (SML)
Problem Solution Results
•More satisfied
shoppers into
the store
•Increase
additional
purchases

10. Case study 2: Cash FLOW Position monitoring
10
Walmart, Amazon, Costco, Carrefour try to manage their cash by avoiding overstocking of non-selling items:
resisting the temptation to buy 10 of an item when only needing 5 just because there is an extra 15% off the cost.
Figuring out a steady stream of items supply and cash flow can be daunting, here is how its presented:
✔ Automatically Integrate supplier
invoice (SE)
✔ Prioritize invoice payments based
on due dates. (SE)
✔ Compare inventory consumption
with supplier invoice (SE)
✔ Build model filtering out supplier,
product, delivery method ,demand,
weather, traffic to maintain a positive
cash flow and optimum stock level
(SML)
Problems Solution Result
•Bad working capital management
•Turnover that is slower than the due
date of the supplier invoice
•Increase in unwanted stocking costs

11. Case study 3: Automate returns in the supply chain
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Not all inventory sold is going to stay sold. Use the Sparta ML platform to build a workflow to easily manage the
return of goods.
✔ Classify most returned items (SE)
✔ Categorize most restocked,
reshelved and resold items after
returns (SE)
✔ Prepare an algorithm that
automatically places most probable
returned items for re-sale on the
second market (SML)
Problems Solution Result
•Surge in online orders generating
more than average returns
•Returns processing is an arduous
task
•Inefficient reverse supply chain
Complete Automation of “Reverse
Logistics” or “Reverse Supply Chain”

12. Integration
Easily integrate with
front-office and
productivity tools like
Salesforce and Slack
Optimize models
Use our no-code ML
model builder to look for
best possible scenarios for
your processes
Competitive advantages
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One Enterprise Suite
Combine the best
enterprise software with a
dedicated intelligent
automation tool powered
by the Sparta ML platform

13. Platforms
13

14. Pricing Model & Combinations
Per User Base
a) 1 -40
b) 41 – 100
c) 101 – 1000
d) 1001 +
Packages
offered
Basic
Gold
Platinum
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We offer Sparta on the AWS Cloud as a SaaS product.
Pricing could vary based on the package level, Platinum being the
most complex; and User base, the price increases as you add more
users into the system.
Reoccurring payments could be based on the companies
preference. Subscribing for the full year could get the company
some savings when compared to the monthly subscribers.
Providing hands-on additional training to help companies fully
maximize their usage will also help us generate revenue. Support
in different packages could also help us additional reoccurring
revenue.

15. Founding Team
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Samuel Molla Kassa, Co-CEO | CTO
Background in Software Development with
extensive experience working for Fortune 500
companies nationwide.
Background in Finance & Enterprise
Optimization with extensive
experience working for Fortune 500
companies nationwide.
Yelekal Solomon, Co-CEO | CFO

16. Thanks!
Any questions?
You can find us at:
sales@iworkplc.com
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Data from:
*PRNewswire
*Forbes.com
*Gartner.com
*Fortunebusinessinsights.com