Data Orchestration and Artificial Intelligence

Accelerating Value Creation through Data Analytics, AI, and Effective Data Management

As value chains evolve, utilizing reliable data is essential. Orchestrating data effectively is crucial for implementing a successful AI strategy, ensuring seamless integration and management across various sources and systems. By embracing this strategy, your business can adapt to change, optimize decision-making, and maintain a competitive edge while fully harnessing AI's potential.

Uncover the competitive advantage by embracing a wide range of AI applications employed by industries' leaders

Boost your business with cutting-edge solutions, including intuitive chatbots like ChatGPT, image recognition software like Google Cloud Vision, and advanced predictive analytics tools like TensorFlow, driving you toward heightened success and a prominent position in your industry.

  • $1,5tn

    Projected AI market size by 2030

  • 97%

    of mobile users are using AI-powered voice assistants

  • 54%

    of executives say that AI solutions have increased productivity in their businesses

  • 3rd

    consecutive year AI is voted as the most impactful new technology among CEOs of top companies

AI, Machine Learning, and Data Science Services at Scale


Deep Learning

Computer Vision

Natural Language Processing

Reinforcement Learning


Chatbots and Conversational AI


Automated Planning

Search and Information Retieval


Deep Analysis

Data Annotation

Statistical Analysis

Predictive Analytics

Data Mining

Time-series Analysis

Causal Analytics

Data Visualozation and Reporing

DATA Science

Unleashing Business Potential: The Benefits of AI and Machine Learning Solutions

With successful implementation of AI/ML solutions, companies can benefit from reduced operational costs, streamlined internal processes, and enhanced sales with unique product features. AI/ML architects analyze business requirements to provide tailored recommendations for organizational improvements, resulting in full value from the AI/ML solution across the enterprise.

Business Advantages of AI/ML

Business Advantages of AI/ML

effective way to identify issues that are easily missed by automated testing

Data analytics and visualization is vital for gaining insights. With the help of machine learning models, organizations can analyze massive amounts of data and predict emerging customer behavior, making proactive responses possible.

Machine Learning Analytics

Machine Learning Analytics

By automating repetitive tests, automated testing can save time and resources

Integrating AI programs for business processes leads to significant improvements. The right AI solution reduces costs, improves customer support, and enhances consistency. Building a prototype (a so-called MVM) can prove the potential value of AI by highlighting efficiency and operational gains achievable with available data.

Artificial Intelligence Data Analytics

Artificial Intelligence Data Analytics

Evaluate software quality across the SDLC, providing critical feedback earlier and enabling higher-quality and faster deliveries.

What are you missing by not having a modern data strategy?

Unlocking Business Potential: The Importance of a Strong Data Strategy.

  • Unlocking Profit Potential with Data

    To stay ahead of competitors, it is crucial to align your data strategy with market demands. A modern data platform enables the delivery of new features and improved customer outcomes. However, building such a solution often requires expertise from multiple vendors and complex solutions. At Architech NYC, our consultants and technicians work to create a tailored data platform that delivers real-time insights.

  • Streamlined Data Handling

    Legacy systems are incapable of keeping up with today's data scale, which limits the potential for maximum business value. Architech NYC works with multiple vendors and platforms to modernize data warehousing, delivering a solution that meets changing business needs. We combine our consulting and technical expertise to pinpoint key business opportunities and create a progressive migration and implementation plan for your new data warehouse.

  • Maximizing the Value of Your Data

    Advanced data visualization, data governance, and AI implementation are critical to derive value from your modern data warehouse. Architech NYC works with leading vendors such as AWS, Google, Microsoft,Tableau, and others to design and implement a custom data solution that aligns with your business needs. Our experts provide a comprehensive approach to help you get the maximum out of your data.

Data Science and AI Solutions for Industries

Transforming Business with Data Science and AI Solutions Across Industries

  • Fintech and Insurance

    • Fraud detection and financial forecasting using predictive modeling

    • Fast and accurate liquidity analysis for risk management

    • Efficient management of insurance claims and credit scoring

    • Customized wealth management using intelligent advisors

    • Tracking of Key Performance Indicators (KPIs) and visualizing performance

    • Detailed analysis of Profit and Loss (P&L) for benchmarking and insights.

  • Marketing

    • Personalized demand prediction and marketing

    • Intelligent customer segmentation

    • Automated real-time data aggregation

    • Real-time optimization and reallocation of marketing budgets

    • Tracking of KPIs and visualization of performance

    • Optimized returns on marketing investments

    • Accelerated reporting and retrieval of information

    • Product recommendation engines

    • Personalized shopping experiences and conversational commerce

  • Ecommerce

    • Intelligent customer service and chatbots

    • Personalized shopping and conversational commerce

    • Demand prediction and targeted advertising

    • Smart inventory control and management

    • RFM analysis and tracking of customer preferences

    • Recommendation engines for shoppers

  • Healthcare

    • Customized patient care and performance analysis

    • AI-assisted pharmaceutical research

    • Real-time medical data processing

    • Streamlined logistics, delivery, and supply operations

    • Automation of diagnostics and risk identification

    • Clinical data analysis through OD technology

    • Tracking of KPIs and performance visualization

    • Safe PHI access for authorized personnel

  • Education

    • Personalization of student experiences

    • Analysis of student achievement data

    • Captioning and accessibility of educational videos

    • Student success analysis and educational planning

    • Building a future-ready enterprise data vault

    • Analysis of customer lifetime value, retention, and attrition

    • Analysis of budget efficiency

  • ERP Software

    • Secure and regulatory-compliant enterprise data storage

    • AI/ML integration to empower ERP systems

    • Analysis of customer lifetime value, retention, and attrition

    • Consistent data architecture ready to scale

    • Digital mapping of the customer journey

    • Streamlined business process automation

  • Transportation and Logistics

    • Warehouse operations automated with data-driven processes

    • Real-time intelligent routing of supply and distribution

    • Predictive maintenance to ensure vehicle reliability

    • Intelligent fleet managemen

    • tReal-time traffic forecasting and updates

    • Automation of supply chain management

    • Tracking of KPIs and visualization of performance


Our process

Help identify patterns and insights that can drive informed decision-making.

The discovery stage involves identifying the problem to be solved, gathering and analyzing data, and determining the feasibility of using AI/ML.In this stage, it's important to define project goals, establish a hypothesis, and explore potential data sources and preprocessing requirements before selecting appropriate algorithms.



In this stage, the team performs cleaning and formatting data, selecting appropriate algorithms, training and testing models, and evaluating results for refinement.



This stage involves translating business requirements into technical specifications, selecting appropriate technologies, and creating a prototype or minimum viable product for testing.

Design and Build

Design and Build

The deployment stage incorporates integrating it into the existing system, testing for functionality and performance, monitoring for errors and updates, and ensuring that the solution meets the desired business objectives.





The team executes the testing of the solution in real-world scenarios, identifies areas of improvement, and implementes necessary changes to improve performance, accuracy, and efficiency. This stage also includes retraining and tuning models for better results.

Practical. Reliable. Proven.