Effective digital supply chains require massive amounts of real-time big data from various sources all around the world. So, why are we still relying on traditional, static principles that don't accurately display the whole picture? TransVoyant's Precise Predictive Logistics and Risk Analysis tools offer an in-depth look at the behaviors of consumers and suppliers to produce the most accurate data available to their clients. Want to know how to generate such massive amounts of information? Read here http://bit.ly/2E8bmNE

1. TransVoyant Continuous Decision
Intelligence™ (CDI™)
The Digital Supply Chain
IoT Hub and Analytics Platform
WE
PREDICT
THE
FUTURE Real-Time
Big Data
Advanced
Analytics
Predictive
Insights
®

2. ©2019 TransVoyant | We Predict the Future
TransVoyant Continuous Decision
Intelligence™ (CDI™)
The Digital Supply Chain
IoT Hub and Analytics Platform

3. TransVoyant’s Precise Predictive Logistics (P2L) and Precise Predictive Risk (P2R) solutions are cloud-based
applications that have intuitive user interfaces, supply chain workflows and pre-packaged insights. As
functionally-rich as these applications are, they are extrapolation and exploitation layers, sitting on top of an even
more powerful core platform called Continuous Decision Intelligence (CDI). CDI is the IoT data collection and
processing hub that feeds data and insights into P2L and P2R, as well as our customers’ complementary systems
which execute our prescriptive recommendations. CDI enables us to deliver transformational results for our Global
2000 and national security customers where others have failed.
Our CDI platform comes complete with the following components, all are must-have capabilities for any supply
chain analytics solution hoping to deliver on the promise of a digital supply chain:
©2019 TransVoyant | We Predict the Future
The Digital Supply Chain IoT Hub and Analytics Platform

4. What is a digital supply chain without the data? How can a supply chain be all-seeing and all-knowing, eliminating
blind spots and latency, and exposing and avoiding risks, without massive amounts of real-time big data? A solution
that doesn’t come complete with big data streams is only half a solution. TransVoyant collects, normalizes and
analyzes over one trillion global data readings around the world every day. Our streaming big data comes from all
types of sensors that continuously snapshot (point in time) behavior of routes, lanes, buffers, nodes,
transportation assets, risks, planes, ships, trains, trucks, weather, road traffic, foot traffic, etc.
Sourcing data from public and proprietary domains is a fundamental capability for TransVoyant and has been part
of the company DNA and process since its founding in 2012. This capability is a key enabler of the end-to-end
real-time visibility and predictive insights we provide for all our clients. As a normal course of business, we add new
live structured and unstructured global data sources to our platform on a continuous basis. We must do this to
support our continuous global behavior machine learning methods and processes that drive value for our supply
chain and risk customers.
©2019 TransVoyant | We Predict the Future
A massive library of real-time big data, collected from
IoT devices around the world and continuously updated

5. CDI Benefits
✓ Obviates the need for companies to collect, cleanse and normalize real-time big data streams from the global IoT
✓ Shortens the time to value for companies trying to digitize their supply chains
✓ Drives significant supply chain efficiencies and savings through predictive insights and prescriptive recommendations
✓ Easily integrates with internal and extended supply chain solutions to become the central point of visibility
and control for global shipments, inventories, orders, demand and risks
✓ Can serve as a company’s central IoT platform across all aspects of the business, not just supply chain
©2019 TransVoyant | We Predict the Future

6. ©2019 TransVoyant | We Predict the Future©2019 TransVoyant | We Predict the Future

7. TransVoyant maintains a Connector Library and a Living Stream Registry that we leverage for connecting to and
ingesting new structured and unstructured data sources as well as managing our existing streams. We also have
normalization, cleansing and proprietary entity resolution and disambiguation algorithms to normalize and repair
both external and customer data. Our underlying IoT Data Hub contains these stream connectors and a stream
registry that allows us to efficiently and securely add new data, a new algorithm, a new microservice, a new
application, a new database, or a new way to export data via API—all the while keeping this distributed data
synchronized for use in prescriptive insights across customer solutions. This allows for quick and proven
integrations with new and unique data sources and isolates the streaming data from changes to the source or
target. Our decoupled asynchronous event streaming architecture provides a unique and highly scalable platform
for sourcing, transforming and streaming data. We treat all data as a stream with individual discrete events. All data
is kept as a raw event, including every single customer inventory reading by SKU, location, bin, etc., as well as every
predicted time of arrival calculated by TransVoyant and every carrier-generated ETA, for example. The data is
stored in both its raw state as well as normalized format to be accessed live and utilized in CDI P2L/R core
algorithms, insights, microservices and applications. In addition, the entire library of live and historical normalized
event data is made available to our insights toolkit to use for new insight creation, model training and back-testing.
This insight creation work is an ongoing disciplined process conducted by our data science and data engineering
teams. Finally, continuously saving the raw and normalized data to our HDFS infrastructure allows history to be
leveraged for playback, forensic and what-if analysis.
©2019 TransVoyant | We Predict the Future

8. Most self-styled digital supply chain applications focus on shipment visibility. By and large, traditional supply chain
visibility providers have established direct connectivity to carriers, collecting, consolidating and displaying
EDI-based shipment status updates. At worst, EDI status updates are human generated, which means they are
subject to keying errors and ‘aspirational’ estimates. We often discover that carriers have been reporting on-time
arrivals to our customers via EDI, when in fact, their actual arrival times are hours or days later than what was
reported. IoT devices don’t lie. An actual time of arrival is an actual time of arrival. Additionally, EDI updates are
processed in batch mode, which means they are notoriously latent. They are not real-time status updates collected
from IoT devices.
©2019 TransVoyant | We Predict the Future
A powerful analytics engine that has been watching and
learning the behavior of supply chains, and the events that
surround them, for years

9. TRADITIONAL SUPPLY CHAIN VISIBILITY
EDI
EDI FAX
EDI HTML
HTMLHTML EDIEDI
EDI
SCV VENDOR ‘B’
SCV VENDOR ‘A’
SCV VENDOR ‘C’
• LATENT DATA
• BLIND SPOTS
• PEER-TO-PEER CONNECTIVITY
• HUB-AND-SPOKE CONNECTIVITY
• CARRIER ONBOARDING
• LOGISTICS TRACKING ONLY
©2019 TransVoyant | We Predict the Future

10. ©2019 TransVoyant | We Predict the Future
True real-time, global supply chain visibility via IoT devices offers organizations distinct advantages, but
transformational results ultimately come elsewhere, from predictive insights and prescriptive recommendations.
While it’s valuable to see the real-time location of a container on a vessel in the middle of the Pacific Ocean, it’s far
more valuable to know when that container is going to arrive at its destination port, be unloaded, clear customs
and be available for pickup. After all, it’s having confidence in that final prediction (available for pickup), weeks
before the vessel hits the destination port, that drives major value in the downstream supply chain. Predictive
insights enable organizations to confidently commit inventory in-transit, in many cases before the goods even
change ownership. It enables organizations to coordinate the arrival of critical parts to manufacturing to avoid
delays and disruptions. It enables organizations to meet tight delivery windows to customers and provide them with
accurate predicted times of arrival.

11. DIGITAL SUPPLY CHAIN VISIBILITY
• REAL-TIME DATA
• ALL MODES & NODES
• ALL SEEING, END-TO-END
• INTERNAL & EXTERNAL DATA
©2019 TransVoyant | We Predict the Future
IOT
• Ocean
• Air
• Road Construction
• Flight Schedules
• Port Congestion
• Severe Weather
• Price Indexes
• Competitor Actions
• Natural Disasters
• Clearance Times
• Temperatures
• Labor Strikes
• Launch Plans
• Promotions
• Inventories
• Price Actions
• Manufacturing Plans
• Customer Orders
• Purchase Orders
• Capacities
• Truck
• Rail
• Parcel
• Barge
• Manufacturing
• Warehouses
• Customers
• Rail Yards
• Airports
• Stores
• Suppliers
• Ports
SATELLITES RADAR
SENSORS SOCIALPHONES
VIDEO

12. How does TransVoyant make such predictions? Our CDI platform has been watching and modeling the behavior of
carriers, routes, lanes, buffers, nodes, transportation assets, risks, planes, ships, trains, trucks, weather, road traffic
and foot traffic for years. We know which carriers are prone to make unscheduled port stops at different times of
the year, on different lanes. We know about turnaround times at ports based upon the number of vessels arriving
and departing, on different days of the week, at different times of the year, under varying weather conditions. We
know how long it takes for trucks to make their way around a city’s beltway at 2 pm on a Sunday when a professional
sporting event kicks off nearby.
THE BIG WINS FROM ANALYTICS
Learned behavior models
Machine learning algorithms
Artificial Intelligence
Cognitive computing
•
•
•
•
Real-time data
All modes and nodes
All seeing, end-to-end
Internal and external data
•
•
•
•
Future lead times and variability
Global precise times of arrival
Probable strike at supplier
Carrier will make unschedules stops
Port will be congested
Competitor running promotion
Promise date to customer will miss
due to delay in manufacturing
•
•
•
•
•
•
•
Dynamic node inventory optimization
Commit inventory in-transit
Source from alternative supplier
Select alternate carrier or mode
Select disruption free land
Take price action
Divert inventory in-transit to meet
customer order and backfill original
shipment with upstream supply
•
•
•
•
•
•
•
DIGITAL SUPPLY
CHAIN VISIBILITY ADVANCED ANALYTICS PREDICTIVE INSIGHTS PRESCRIPTIVE ACTIONS
©2019 TransVoyant | We Predict the Future

13. ©2019 TransVoyant | We Predict the Future
Only by modeling the behavior of these entities for years, and establishing living, breathing behavior models can a
solution generate accurate predictions. That’s what makes CDI so powerful and uniquely singular.
CDI establishes learned behavior models for...
• Your own supply chain nodes (manufacturing facilities, warehouses, truck fleet, physical and online stores, etc.);
• Your extended supply chain network (ocean ports, airports, roads, railheads, customs clearance points);
• Your extended supply chain partners (suppliers, carriers, brokers, customers);
• The dynamic external events that surround your supply chain (severe weather, natural disasters,
road construction, civil unrest, labor strikes);

14. In addition to being the underlying supply chain analytics platform powering P2L and P2R, CDI is a living IoT Data
Hub. It is the central platform that ingests all internal and external supply chain related IoT data across a company.
As such, CDI has rich pre-built APIs, designed to ingest massive amounts of external IoT data that TransVoyant
collects around the world every day. This includes the internal data that we collect from our customer’s systems
(i.e., inventory positions, purchase orders, point of sale data, etc.) and the prescriptive actions that we pass back
to our customers’ ERP and supply chain planning & execution systems for instantiation. Our connector/processor
architecture is structured around a decoupled microservices strategy; with the goal of minimizing and controlling
the impact of changes to linked environments. The benefit to our customers is that the underlying microservices
can be easily modified, updated and expanded without taking the entire system down. Additionally, as volumes
expand and variables change or grow the microservices are adapted accordingly.
Pre-built APIs that ingest internal and external big data
streams, and pass predictive and prescriptive insights to
complementary systems for execution
©2019 TransVoyant | We Predict the Future

15. ©2019 TransVoyant | We Predict the Future
TransVoyant CDI is a cloud-based platform with limited infrastructure impact on client environments. The solution
auto-scales, load balances and has global redundancy. It is a 100% containerized, automated, self-healing
infrastructure that can automatically provision, configure, monitor, and dynamically allocate resources. While CDI,
P2L and P2R run in the cloud, it is straightforward to deploy on premises, if needed. CDI is a battle-tested
infrastructure, handling massive volumes with multiple synchronized availability zones, fault tolerant, parallelized
to eliminate single point of failure and trusted by national security and Global 2000 customers. As more and more
organizations are recognizing the transformational value of digital supply chains, new technology providers are
emerging at an accelerated rate. Across the board, the go-to-marketing messaging for these vendors has become
remarkably similar, making it difficult for organizations to differentiate between vendors and to choose a proven
partner capable of delivering results.
A technology infrastructure that is cloud-native, can scale to
massive volumes and processes at lighting fast speeds

16. Based on our experience with Global 2000 companies,
the proof is in the platform.
©2019 TransVoyant | We Predict the Future©2019 TransVoyant | We Predict the Future
• Digital supply chains require massive amounts of real-time big data continuously sourced from IoT devices around
the world, cleansed, normalized, healed and formatted for processing by a powerful analytics engine.
• The analytics engine needs to understand the current and future behavior of carriers, routes, lanes, buffers,
nodes, transportation assets, risks, planes, ships, trains, trucks, weather, road traffic, foot traffic, under varying
conditions. Only through learned behavior models, established over years, and continuous updating, can
a solution produce accurate predictive insights and prescriptive recommendations.
• A supply chain analytics platform must have pre-built APIs, capable of ingesting external data from IoT devices,
internal data from ERP and other systems, and passing prescriptive recommendations to supply chain planning
and execution systems for instantiation.
• A cloud-native technology infrastructure capable of processing massive volumes at lighting fast speeds,
with enterprise class security and fault tolerance.

17. Precise Predictive Logistics [P2L]
• Control Tower
• User Interface
• Drill Down/Search
• Workflow
• Collaborative Issue Resolution
• Reporting
TransVoyant Insight Foundry
Precise Predictive Risk [P2R]
• Control Tower
• User Interface
• Drill Down/Search
We deliver our insights
and recommendations
in a visual control tower/
interactive UI with
workflow, collaborative
issue resolution
and reporting
INTERACTIVE
CONTROL
TOWER / UI
We have library of
pre-packaged insights
related to global supply
chain behaviors, risks
and opportunities
We continuously produce
new customer-driven
insights
•
•
•
INSIGHTS
• Workflow
• Collaborative Issue Resolution
• Reporting
• Pre-Packaged Insights • Customer-Driven Insights
6
5

18. Future State Modeling
• Dynamic Network Discovery
• Machine Learning Optimization
• What-If Modeling
• Predictive Modeling
• Correlation Analysis
• Pattern of Life
Risks and Impact from External Events
We predict disruptions,
identify oppotunities and
generate prescriptive
recommendations that
optimize supply chain
performance
PREDICTIONS &
PRESCRIPTIVE
ACTIONS
We overlay our
current and predicted
understanding of
external events on top
of our customers’
shipments and supply
chain nodes
•
•
RISKS FROM
EXTERNAL
EVENTS
4
3
• Natural Disasters
• Labor Strikes
• Temperatures
• Severe Weather
• Competitor Actions
• Price Indexes
• Post Congestion
• Consumer Foot Traffic
• Sun-Glare
• Wind Speeds
• Wave Heights
• Civil Unrest
• Custom Clearance Times
• Flight Schedules
• Air Traffic
• Road Construction
• Traffic Accidents
• Geopolitical Trends
OPTIMIZED
PREDICTIVE

19. Real-Time Visibility of Your End-to-End Supply ChainREAL-TIME
We provide our
customers real-time
visibility of the
supply chains
We learn the behavior
of their supply chains
over time to constantly
improve our predictions
REAL-TIME
BEHAVIOR -
CURRENT STATE
We collect massive
external data streams
from IoT devices
We analyze these
streams over time and
produce learned
behavior models
We fuse our data streams
and learned behavior
models with our
customer’s internal data
We continuously analyze
these fused data sets
to product real-time
visibility, predictive
insights and
prescriptive actions
•
•
•
•
•
•
DATA COLLECTION
& ANALYSIS
2
IoT Data Hub - Continuous Decision Intelligence (CDI)ALL SEEING 1
• Inbound
• Outbound
• Internal Systems
• Trading Partners
APIs
• Internal Nodes
(DC, Factory, Store)
• External Nodes
• Carriers
• Borders/Customs
LEARNED BEHAVIOR MODELSANALYTICS, MACHINE LEARNING &
ARTIFICIAL INTELLIGENCE INFRASTRUCTURE
ERP Video Satellites Radar Phones Meters News Social Telematics Sensors WeatherPOS SCM Product/Price
DATA FROM INTERNAL SYSTEMS REAL-TIME BIG DATA FROM IoT

20. ©2019 TransVoyant | We Predict the Future
To learn more visit www.transvoyant.co