WhiteSpace

Scaling up the startup despite the pandemic? 
Ekohe brings exponential growth to on-demand meeting space innovator. 

Cyber Security Leader

Securing a bright future for Europe's cyber defense powerhouse.

Because We Care

Ekohe's custom ChatGPT empowers BWC to stand tall in wellness, via an innovative, interactive, self-learning app.

Pulse Insights

From startup to B2B market leader at light speed, through an innovative Voice of Customer survey engine.

Essence Wave

Empowering a chemistry industry leader with cutting-edge AI 

Host Broadcast Services

ERP Powering Broadcast & Event Infrastructure for the World's Largest Sporting Event Since 2008.

IDEO

From web registration to managed services, IDEO found a trusted partner to support its growth in China — for 8 years and counting.

Podknife 

Reimagine Podcasting: How NLP fostered an open, holistic ecosystem for audiences, brands and creators.


Fitnext

Helping wellness startup define, rapidly prototype, and launch an expert-driven, deeply personalized diet & exercise app.

International Cosmetics Leader

Centralizing data insights to optimize efficiency, boost sales, and enable market scale for international cosmetics leader.

Building the world's largest centralized development platform: 15,000+ innovations, $1.5+ billion funded.

Building and optimizing models tailored to specific business needs, enabling data-driven decision-making

Machine Learning Model Development

Leveraging advanced neural architectures to process complex patterns and large datasets with high accuracy

Deep Learning & Neural Networks

Predicting future trends and behaviors using historical data to drive strategic insights

Time Series Analysis & Forecasting

Creating individualized customer experiences through automated, data-driven marketing campaigns and content tailored to user preferences

AI-Driven Personalization

Enabling AI to understand, interpret, and generate human language for applications like chatbots, translation, and summarization

Natural Language Processing (NLP) & Large Language Models (LLMs)

Developing autonomous AI systems that can plan, adapt, and make decisions independently

AI Agents & Automation

Extracting and integrating data from various sources to power applications, analytics, and automation.

Data Scraping & API Integration

Ensuring data quality, security, and compliance through structured policies and best practices.

Data Management & Governance

Turning raw data into actionable insights to drive informed decision-making and strategy.

Business Analytics & Intelligence

Using historical data and machine learning to anticipate trends and future outcomes.

Predictive Analytics & Forecasting

Designing and deploying scalable cloud solutions across leading cloud providers

AWS, Google Cloud, OVHCloud & Aliyun infrastructure deployments

Designing seamless interactions across all touchpoints to improve customer satisfaction and loyalty

Customer Experience  & Service Design

Transforming business processes from Excel-based workflows into robust database architectures, modeling complex business logic into scalable data structures

Database Engineering

Implementing flexible, iterative development processes to enhance collaboration and efficiency.

Agile Methodology/Scrum

Building tailored software solutions for established businesses to streamline operations and solve complex organizational challenges

Custom Enterprise Software Development

Establishing frameworks to manage regulatory, operational, and security risks effectively.

Governance, risk & compliance

We present a semi-supervised Vision Transformer (ViT) framework designed for the automated classification of reflection high energy electron diffraction (RHEED) images of ferroelectric nitride (ScAlN) materials produced by molecular beam epitaxy (MBE). This innovative approach leverages pseudo-labeling, significantly decreasing the reliance on extensive manual annotations while ensuring strong performance across various substrate angles.

Our research investigates the impact of three critical hyperparameters: the proportion of labeled data, the number of Transformer heads, and the model's depth, on classification results. The results indicate that while careful tuning of these parameters can lead to slight improvements in accuracy, simpler configurations—such as using two heads and two layers—strike an optimal balance between performance and computational efficiency. Additionally, fine-tuning embedding dimensions enhances the model further without imposing heavy computational demands.

Importantly, our semi-supervised framework achieves comparable or superior accuracy compared to fully supervised methods while requiring significantly fewer labeled samples. This adaptability across different RHEED angles showcases the framework’s versatility and effectiveness. 

These findings emphasize the transformative potential of semi-supervised ViT-based solutions in advancing AI-driven standardization and optimization processes within semiconductor manufacturing, streamlining workflows, enhancing efficiency, and ultimately contributing to cost reductions in the production of advanced materials.

Semi-Supervised Vision Transformer Framework for AI-Based RHEED Image Classification of Ferroelectric Nitride MBE Growth - ACS Publications

**Creating tailored digital solutions to improve efficiency in chemical production and quality assurance using AI**

_Chemical operations are complex, data-heavy, and sensitive to inefficiencies
R&D teams and manufacturers need better tools to accelerate discovery, reduce waste, and maintain consistent quality_

We provide **AI models, predictive analytics, and custom software** to support smarter decision-making in chemical processes


AI in chemicals market size is projected to grow from $2.29 billion in 2025 to around $28 billion by 2032

AI in Chemicals Market

AI-driven optimization is expected to reduce energy use and waste in chemical manufacturing by up to 20% by 2030, aligning with global sustainability targets

Energy & Waste Reduction

77% of chemical executives expect blockchain integration within 1–3 years, with 71% calling it critical for future-proofing operations, transparency, and supply chain resilience

Blockchain Adoption Readiness

Future trends

Chemicals

Creating tailored digital solutions to improve efficiency in chemical production and quality assurance using AI

We can build platforms that analyze lab results, simulations, and chemical data to identify promising compounds faster

Accelerated R&D and Material Discovery

We provide real-time monitoring and predictive models that optimize production settings and minimize downtime

Smart Manufacturing & Process Optimization

We can automate analysis of lab reports and test data to flag anomalies and maintain compliance

Quality Assurance Automation

We offer tools to track environmental metrics and ensure operations meet evolving regulatory standards

Environmental & Regulatory Monitoring

We deliver AI solutions that align production planning with predicted demand to avoid stockouts or overproduction

Demand Forecasting and Inventory Planning

We create tailored tools to manage experiments, standardize reporting, and centralize research knowledge

Chemicals

Future trends

$0B+

AI in Chemicals Market

0% ↓

Energy & Waste Reduction

0%

Blockchain Adoption Readiness