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FORTUNE - 2023

America’s most innovative companies

LATEST NEWS: Revolutionizing Business Intelligence (BI): Instant Insights with
GenAI

IMPLEMENTING ENTERPRISE AI,
A STRATEGIC APPROACH

While the promise of Enterprise AI is significant, realising it's potential
requires a thoughtful and strategic approach. Organizations must align their
strategic objectives with the capabilities provided by Wide Data, Discriminative
AI, and Generative AI. Furthermore, the right infrastructure, skills and
policies must be in place to effectively manage and utilize these tools.

CUPP Framework
Wide Data
Generative
AI
Discriminative
AI
GRC

IMPLEMENTING ENTERPRISE AI,
A STRATEGIC APPROACH

While the promise of Enterprise AI is significant, realising it's potential
requires a thoughtful and strategic approach. Organizations must align their
strategic objectives with the capabilities provided by Wide Data, Discriminative
AI, and Generative AI. Furthermore, the right infrastructure, skills and
policies must be in place to effectively manage and utilize these tools.

WIDE DATA

Wide Data forms the bedrock of the Enterprise AI solution. Unlike traditional
big data, which focuses on volume, Wide Data integrates diversity and veracity
along with volume. Wide Data is integrating diverse data sources, providing a
comprehensive view of business environments and markets. By aggregating data
from various sources - transactional data, customer behaviour, environmental
factors, and global trends - businesses can gain a holistic understanding of the
dynamics that drive their operations and markets.

Findability Sciences has partnered with Snowflake, IBM C4D, Yellow Brick, Watson
Openpages and SAP, in addition to many data suppliers, to support Wide Data
implementations.

GENERATIVE AI

Generative AI, a ground breaking technology, uses advanced algorithms to create
new data that mimics the characteristics of the original data. This ability of
Generative AI to produce novel, high-quality data can be instrumental in
improving simulation models, creating synthetic datasets, enhancing customer
experience, and more. By incorporating Generative AI, Findability Sciences
Enterprise AI offering stands at the forefront of innovation, redefining
business solutions.

Findability Sciences Generative AI uses foundation models from OpenAI, Microsoft
Azure, IBM WatsonX, Hugging Face, Google Bard and LangChain.

DISCRIMINATIVE AI

With a wealth of data collected through Wide Data, Discriminative AI comes into
play. This form of AI is adept at identifying patterns and making correlations
within complex data sets. It enables businesses to accurately predict market
trends, optimise operations, and make strategic, timely decisions, thereby
positioning the company for increased success.

Findability Sciences Discriminative AI uses some of these popular algorithms
such as Support Vector Machines(SVMs), Logistic Regression, Deep natural
Networks(DNNs), Convolutional Neural Networks(CNNs), Random Forest, Gradient
Boosting Machines(GBMs), K-nearest neighbours(KNN) and Linear Discriminant
Analysis(LDA).

CUPP FRAMEWORK

 * Collection: This involves gathering data from various sources, laying the
   groundwork for subsequent stages of data processing.
 * Unification: In this stage, data from different sources is consolidated and
   harmonized, ensuring a consistent view of data across the organization.
 * Processing: This encompasses the application of AI algorithms to the unified
   data, gathering actionable insights.
 * Presentation: Here, insights are visualized or presented in a format that is
   easily interpretable by decision-makers, enabling them to leverage the
   insights effectively.

GRC

The adoption of AI solutions necessitates a robust Governance Framework to
ensure data privacy, security and ethical AI usage. Findability Sciences
Governance, Risk and Compliance (GRC) Framework takes into account all these
aspects, providing a secure environment for Enterprise AI operations. It defines
policies and procedures for data access, utilisation and disposal, ensuring
compliance with relevant laws and regulations.

Findability Sciences GRC solution is powered by its Discriminative AI and IBM
Watson Openpages.


ENTERPRISE AI FOR MANUFACTURING

Findability Sciences used multi algorithmic time-series forecasting solution to
stabilize the volume and value prediction accuracy at 90% and above.


PROBLEM


SOLUTION


OUTCOME

One of North America's leading providers of HVAC solutions wanted to optimize
inventory planning and predict sales for 250+ geographically dispersed
locations. A vast product portfolio of over 1100 SKUs. Stock- outs resulted in
high warehousing and holding costs. Need for demand forecasting and inventory
management for distribution centers.

Watch Video


ENTERPRISE AI FOR MANUFACTURING

Findability Sciences used multi algorithmic time-series forecasting solution to
stabilize the volume and value prediction accuracy at 90% and above.


PROBLEM


SOLUTION


OUTCOME

One of North America's leading providers of HVAC solutions wanted to optimize
inventory planning and predict sales for 250+ geographically dispersed
locations. A vast product portfolio of over 1100 SKUs. Stock- outs resulted in
high warehousing and holding costs. Need for demand forecasting and inventory
management for distribution centers.

Watch Video

MEDIA

BFSI

HEALTHCARE


ENTERPRISE AI FOR MANUFACTURING

Findability Sciences used their multi algorithmic time-series forecasting
solution to stabilize the volume and value prediction accuracy at 90% and above.


PROBLEM

One of North America's leading providers of HVAC solutions wanted to optimize
inventory planning and predict sales for 250+ geographically dispersed
locations. A vast product portfolio of over 1100 SKUs. Stock- outs resulted in
high warehousing and holding costs. Need for demand forecasting and inventory
management for distribution centers.


SOLUTION

A custom forecast solution was developed using learning and deep learning
algorithms. They were ensembled to obtain higher accuracy against the
traditional time-series forecasting algorithms. A dashboard was created to view
forecast outcomes at different granularities.


OUTCOME

Forecasting accuracy improved to 90%. Up to 10% reduction in stock-out
incidents. Substantial revenue benefit. Scaled up to prediction of sales for
1100+ SKUs across 250+ locations.

Watch Video


ENTERPRISE AI FOR MEDIA

HT Media increases conversions by upping CTR by 8% with Findability's AI driven
consumer insights


PROBLEM

One of India's leading media conglomerated, owning some of the country's largest
digital publishing platforms for news, lifestyle, and entertainment content,
wanted to improve their audience engagement across multiple online platforms. A
positive audience experiences, in terms of people being able to discover and
consume relevant content, was an important driver of audience engagement,
leading to increased average advertising revenue per visitor. The client's
digital publishing platforms hosted a variety of content including news,
editorials, critics' reviews, picture and video galleries.


SOLUTION

A content recommendation system was developed for five digital properties, to
offer personalized content suggestions to website/app/platform users. The
recommender system algorithm was trained using a combination of unsupervised
machine learning and reinforcement learning. It provided content suggestions
upon processing live, click-stream data.


OUTCOME

Key audience engagement metrics such as the click-through rate (CTR), page views
and bounce rate showed improvement for all the platforms where the recommender
system was adopted. The improvement in CTR ranged from 6 to 8%.

Watch Video


ENTERPRISE AI FOR BFSI

AI Driven Propensity to Pay Solutions from Findability Sciences


PROBLEM

A global accounts receivable management company wanted to optimize the
collection of overdue credit card balance for a fortune 500 retail firm.
Headquartered in US, the retail corporation is among the top 10 in the country,
and issues their own branded credit cards to the members of its loyalty program.
Consumers purchasing through these store-credit are rewarded with upfront
discounts, extended exchange period, free shipping, and so on. Each year, an
estimated 25,000 consumers accrue a cumulative debt ranging between USD 40 to 45
million, in overdue payments.


SOLUTION

A tele-calling strategy was formulated based on a combination of ageing of debt
and payment propensity score to improve the yield of collections. Each overdue
debtor in the portfolio was assigned on AI-based 'propensity to pay' score using
Findability.AI, a proprietary suite of machine learning, NLP and computer vision
technologies from findability Sciences.


OUTCOME

The adoption of AI-driven debtor contact strategy has resulted in 20 to 30%
uplift in YOY collections, observed over a period of 2.5 years. A significant
increase was witnessed in collections for the older debt-age buckets, while
keeping the capacity constant. The client realized a financial ROI of >40% for
the year 2021.

Watch Video


ENTERPRISE AI FOR HEALTHCARE

Straumann unlocks hidden operational efficiencies with Findability's AI
solutions.


PROBLEM

Straumann was looking at building the implant market leadership and wanted to
harness data with AI to revolutionize patient care, but was struggling with
unstructured data overload. Building a data architecture powered by AI would
create a prediction engine for optimal business outcomes.


SOLUTION

Findability built a frame to harness volumes of data gathered over the years to
measure performance through KPIs as fill rate, engagement quality and Net
promoter score. The power of AI was then leveraged by Straumann to expedite its
digital transformation journey.


OUTCOME

The information architecture built by Findability helped Straumann drive
operational decisions to become the most innovative customer-centric oral care
business. Backed by AI- driven insights, the group is now making strong inroads
in digitizing treatment workflows creating a frictionless experience for
patients.

Watch Video

Unlock the potential of your business with our cutting-edge enterprise AI
Offerings

Discriminative AI
Solutions

Data Management
Solutions

Generative AI
Solutions

GRC


Discriminative AI Solutions

Findability Sciences leads the shift from traditional automation to AI-powered
systems. We use Machine Learning, Natural Language Processing, and Computer
Vision, combined with our unique frameworks—Wide Data and CUPP™—to deliver
top-notch Discriminative AI Solutions. These solutions are experts at making
accurate predictions by analyzing all types of data from various sources. Our AI
technology is self-learning and highly accurate, making us stand out in sectors
like healthcare, finance, and marketing. Discriminative AI helps businesses spot
crucial patterns and opportunities for informed decisions. In a rapidly changing
market, our AI solutions guide businesses through big data challenges, ensuring
they operate efficiently and accurately.

Demand Forecast | Price Prediction | Employee Behaviour Forecasting | Risk
Prediction | Propensity Prediction | Churn Management | Recommendations |
Summary | Chatbot

Learn more
Generative AI Solutions

In today's world, where data is as valuable as oil, advanced Data Management
Solutions are essential. As we deal with increasing amounts of diverse data from
both internal and external sources, managing it becomes more complex. It's not
just about the amount of data, but also its variety. We need to combine
structured data, like transaction records, with unstructured data, such as
social media posts or customer feedback. Enterprise Data Management Solutions
help organize this mix of data. They ensure its quality, security, and
compliance while allowing for real-time analysis. This gives businesses a
complete view of their operations and customer interactions. In a competitive
market, having a solid data management plan isn't just a bonus—it's key to
long-term success. It helps businesses remain adaptable, compliant, and driven
by data.

Machine Learning | Natural Language Programming | Computer Vision | Micro
Products

Learn more
Data Management Solutions

Enterprises should consider taking a Foundation Model and fine-tuning it on
their organization's custom content for a myriad of compelling reasons. Foremost
among these is the promise of heightened privacy and security. When
organizations train models on their proprietary data, they retain complete
control over data access, ensuring that sensitive information remains confined
within the company's infrastructure. This mitigates the risks of data breaches
and unauthorized access. Additionally, by customizing a pre-trained model,
businesses can tailor its capabilities to align perfectly with specific
organizational needs, ensuring the AI solution is uniquely optimized for the
company's tasks. This not only delivers better performance and accuracy but also
facilitates faster decision-making and reduced overheads. Moreover, building
upon a Foundation Model allows businesses to leverage the vast general knowledge
embedded within it, while at the same time harnessing the power of
customization. This combination ensures both broad-based understanding and niche
expertise, offering the best of both worlds.

Data Logistics | Data Modernization | SAP Focused Services

Learn more
GRC

Findability Sciences revolutionizes Governance, Risk, and Compliance (GRC) with
AI-driven solutions, turning these areas into powerful assets that significantly
boost business value and Return on Investment (RoI).

Learn more

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Discriminative AI Solutions
Demand Forecast Price Prediction Employee Behaviour Forecasting Risk Prediction
Propensity Prediction
Churn Management Recommendations Summary Chatbot
Data Management Solutions
Data Logistics Data Modernization SAP Focused Services
Generative AI Solutions
Machine Learning Natural Language Programming Computer Vision Micro Products
Governance, Risk & Compliance Government Solutions About Us Careers Latest News



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