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Automated Data Logistics & Advanced Machine Learning Techniques
Our automated, no-code prediction platform streamlines the AI model development and validation process, saving substantial time and effort. Craft and deploy rapid, low-latency solutions tailored for real-time or near real-time applications, enabling prompt and informed decision-making.
Problem
A premier HVAC solutions provider in North America aimed to refine inventory planning and enhance sales predictions across more than 360 locations. The complexity was heightened by a diverse product range exceeding 6,600 SKUs, where stock-outs were leading to elevated warehousing and holding expenses.
Solution
To address this challenge, a specialized forecasting solution was engineered, leveraging both machine learning and deep learning algorithms. These techniques were combined in an ensemble approach to achieve superior accuracy over traditional time-series forecasting methods, offering a strategic advantage in inventory management and sales forecasting.
Accuracy
SKUs
Locations
Problem
A top-tier microelectronics component manufacturer aimed to refine SKU-level pricing strategies for trade sales. Their existing price prediction algorithm was plagued by bugs, leading to extended processing times. The goal was to suggest price points that enhance the chances of winning transactions, thereby maximizing revenue without sacrificing profit margins.
Solution
Findability Sciences deployed its machine learning technology to analyze historical data on revenue, quantities, price points, deal success rates, and forecasted demand. This enabled the recommendation of optimal price points for each SKU.
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Accuracy
Reduced Time
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Problem
A Japan-based multinational aimed to reduce employee churn and improve mentorship but struggled to identify root causes of voluntary attrition despite development investments.
Solution
Findability Sciences structured graphical IoT sensor data into CSV files, built ML models to predict breakdown timestamps, and used time series analysis to identify failure patterns and key influencing factors.
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Accuracy
Maximize
Increased
A Top 5 retailer requires digital analytics for 4000 feature releases annually
Their analysts would require 8 weeks to provide analytics on the impact created by a website feature release. These were manually computed, based on just a differential between impressions and conversions. The FS incrementality computation included seasonality, attribution, and statistical significance. Business users could gain instant insights through a conversational interface. Additionally, forecasts were generated with a 22% uplift compared to internal accuracies for all product conversions to detect anomalies after a release.
Accuracy
Stat Sig
Time Saved
Problem
Traditional HVAC distributors struggle with fragmented systems, manual reconciliation, and reactive inventory planning. Poor data visibility leads to excess stock, frequent stockouts, and high fulfilment costs. Seasonal fluctuations and supply chain disruptions amplify inefficiencies, draining capital and reducing service levels across regions — making agility nearly impossible
Solution
Findability Sciences’ Inventory Agentic Workflow Engine (AWE) integrates real-time data from all enterprise systems to enable proactive, AI-driven inventory management. With Forecasting, Segmentation, and Planning Agents, enterprises gain SKU-level precision, simulate demand scenarios, and dynamically optimize replenishment, routing, and placement — transforming operations from reactive to predictive
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Savings
Inventory Turns
Lower Carrying Costs
Forecasting of 8 real estate parameters for 24 months with over 90% accuracy
The biggest challenge for a real estate asset management company in the US was forecasting market conditions for investment and divestiture decisions. By forecasting rent, occupancy, and value with over 90% accuracy for 24 months, the company was able to use the forecasts for making financial and investment decisions. Additionally, an economic downturn forecast was conducted to determine the probability of a recession in 6 months, 12 months, and 24 months with 94% accuracy.
Accuracy
Forecasts
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Let’s transform your enterprise with data-driven, autonomous intelligence.