Forest Wildfire Spread Prediction

Forest Wildfire Spread Prediction
Customer

World Wildlife Fund (WWF)

Developed a wildfire prediction system in collaboration with WWF to anticipate wildfire in Bolivian forests through a new fuel model based on geo data

Challenge

  • Bolivian forests are at a high risk of wildfire
  • Wildfire prediction system needed to anticipate how a fire might start and where it will spread

Solution

  • Used publicly available data such as weather, climate, past fires, and geo data to model the wildfire spread starting at a certain point in time
  • Created a new fuel model for Bolivia by transferring knowledge from available US data

Business impact

  • A complete fuel model for the Bolivian territory is now available
  • Applications created enable visualisation of past fires
  • Discovered main pain points of ML with geo data and established a clear plan on how to tackle them and speed up future use cases

Summarization and Information Retrieval with OpenAI

Customer

Internal Project

Combining Azure Cognitive Search & Azure OpenAI services to summarize key insights from documents and provide answers to medical-related questions

Challenge

  • The recent release of OpenAI services on Azure has made a lot of noise in the broader world with interesting use cases being tested.
  • Despite that, the industrialisation and implementation of such services in concrete business applications is still to see

Solution

  • Articles relevant to a user question are identified and retrieved using Azure Cognitive Search.
  • The retrieved articles are fed to Azure OpenAI services. The output consists of a summary with references to articles used in the answer.
  • The scope of the retrieved documents and the chatbot responses is limited to the medical domain.

Business Impact

  • Speeding up information retrieval and summarizing key insights from a large amount of structured and unstructured data
  • On client demand, information can be extended to other public sources or using only internal sources of a company data

Converting Text to Query via LLM Chatbot

Customer

Multinational Consumer Electronics

Designed an LLM-powered workflow for the customer team to analyze user behaviour

Challenge

  • Convert natural-language questions into SQL code, run it on the database, and return results to user
  • Ensure accuracy and efficiency in processing complex queries while maintaining data privacy and security
  • Provide training and support to the analytics team to effectively use the chatbot and interpret the results.

Solution

  • Multi-step workflow breaking the problem into smaller tasks
  • Dynamic selection of relevant examples shown to the LLM using a Vector database
  • Fine-tuning the LLM on specific use cases
  • Accuracy uplift through prompt engineering

Business Impact

  • Democratizing data access & analytics to non-technical professionals
  • Improved understanding of state-of-the-art approaches to LLM text-to-SQL task
  • Improved ability to assess challenges and feasibility of reproducing the project for other text-to-SQL use cases
  • Potential for increased efficiency and accuracy in generating SQL code from natural language queries

Causal Inference Library

Developing internal causal inference library
Customer

Multinational Consumer Electronics Company

Developing internal causal inference library consisting of 10+ algorithms and applied library to 2 use cases

Challenge

  • Build causal inference library to be used by other data scientists in the future for various projects
  • Enable activities such as churn analysis and A/B testing to be conducted

Solution

  • Developed library in collaboration with internal stakeholders, did unite testing/documentation/user guide
  • Worked on two related use cases needed for the analysis
  • Unit8 implemented 60% of the algorithms for the project

Business impact

  • Library enables data scientists to easily use multiple algorithms for causal inference through a unified API design
  • 10+ algorithms implemented

Due Diligence Tool

Due Diligence Tool
Customer

US Law Firm

Building an application to streamline the due diligence process through a combination of automated web searches and web scraping

Challenge

  • Client offers due diligence as a service
  • Due diligence process is multi-tenant; users from multiple separate parties work together
  • Process slowed down by back-and-forth communication and repetitive tasks
  • Goal was to automate due diligence process

Solution

  • Built a multi-tenant application to streamline the due diligence process end-to-end
  • Implemented automated web search, website scraping and screening of entities linked to the target company

Business impact

  • Project still in deployment, no impact available at this time

Supply Chain Demand Forecasting

Supply Chain Demand Forecasting
Customer

Medical Equipment Manufacturer

Building a forecasting model for a medical equipment manufacturer resulting in significant forecasting accuracy improvements allowing better procurement planning and contract management

Challenge

  • Forecasting challenges when it comes to their supply chain
  • Demand Planners working very manually with back and forth between planners, sales, and manufacturing
  • Goal is to improve this with a more intelligent tool

Solution

  • Built forecasting model with features included in Darts in combination with hierarchical reconciliation
  • Solution would stream data directly from SAP

Impact

  • Forecasting improvements of 10-60% compared with historical forecasting methods, depending on the time outlook in the model
  • Helps procurement negotiate better contracts with suppliers and plan manufacturing accordingly

Data Management, Forecast, and Visualization on Foundry

Customer

Swiss Raw Material Vendor

Demonstrated how a cloud platform can ingest different data sources and made dashboards and applications that could drive strategic decision-making

Challenge

  • Client wanted to have a view of the current raw material inventory in the warehouse
  • Need to forecast the inventory on customer side in order to optimize production and logistic cost and to increase customer satisfaction

Solution

  • Data ingestion from different data sources including SAP, MeteoSwiss, and IoT devices
  • Using Supply Chain offerings to define ontology
  • Clean data
  • Apply forecasting models through our Darts library

Business impact

  • Showcase different forecasting models alternatives
  • Optimized warehouse logistics
  • Reduced excess inventory stock

Supply Chain Control Tower

Supply Chain Control Tower
Customer

International Reseller

Building a tool to provide a 360° view over the whole supply chain, coupled with an alerting system when a certain material is reaching low stock levels

Challenge

  • Recurrent struggle with materials being out of stock resulting in significant loss in sales

Solution

  • Built application enabling users to see the whole supply chain, either globally or per material
  • Implemented an alerting system that reports when a certain stock level is low and will soon need replenishment

Impact

  • Reduction of average out-of stock levels at a given point in time by about 50%
  • Lowered loss of turnover due to materials being out of stock

Foundry Onboarding

Foundry Onboarding
Customer

Nutrition startup

Onboarding a company on Foundry by providing personalised coaching and helping them implement an initial use case

Challenge

  • Company recently acquired Foundry and the engineers lack the knowledge to launch an initial project

Solution

  • Provided coaching to the engineers to teach them how to use Foundry’s capabilities
  • Helped the engineers launch an initial project and create a minimum viable product

Impact

  • Empowered internal engineers to use Foundry to its full potential on their own
    Completed end-to-end implementation of a minimum viable product, from data ingestion to dashboards

Wildfire spread prediction

Wildfire spread prediction
Customer

WWF (World Wide Fund for Nature)

Problem

  • Wildfires can pose threats to ecosystems throughout the world, but in South America, the effects of deforestation can be particularly severe.
    organizations like WWF Bolivia and FAN constantly seek to improve their threat-modelling capabilities.

Solution

  • Unit8 joined forces with WWF and Bolivian FAN NGO to leverage technology to help predict the spread of wildfires
    Our key objective was to identify and implement technological solutions that could supplement the existing work of WWF and FAN in the detection, modeling, and elimination of wildfire threats.

Impact

  • The goal of the collaboration is to obtain faster reaction times to help authorities decide which zones and communities should be evacuated, and when.

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