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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.
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 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, 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.
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).
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.
Findability Sciences used multi algorithmic time-series forecasting solution to stabilize the volume and value prediction accuracy at 90% and above.
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.
Findability Sciences used multi algorithmic time-series forecasting solution to stabilize the volume and value prediction accuracy at 90% and above.
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.
MEDIA
BFSI
HEALTHCARE
Findability Sciences used their multi algorithmic time-series forecasting solution to stabilize the volume and value prediction accuracy at 90% and above.
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.
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.
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.
HT Media increases conversions by upping CTR by 8% with Findability's AI driven consumer insights
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.
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.
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%.
AI Driven Propensity to Pay Solutions from Findability Sciences
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.
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.
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.
Straumann unlocks hidden operational efficiencies with Findability's AI solutions.
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.
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.
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.
Unlock the potential of your business with our cutting-edge enterprise AI Offerings
Discriminative AI
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Data Management
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Generative AI
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GRC
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.
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.
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.
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).