Design Intelligent Solutions With Our AI & ML Development Service

AI & ML Software DevelopmentWe at BigOh offer AI and ML software development services across the globe to help our clients get top-notch products that will perfectly align with their business goals. Our AI/ML application development services serve your all business needs.  

We follow simple steps that make your software delivery process intelligent and fast.   

  • Problem identification   
  • Product discovery workshop   
  • Production of AI/ML solution

    Contact for Free Consultation!!

    Artificial Intelligence & Machine Learning Development Services

    Why Choose Our AI & ML Development Services?

    robust tools and technologies

    Robust Tools and Technologies

    We use latest tools and technologies including Python, Tensorflow, AWS, Azure - Cognitive, IBM - Waston- PAAS to provide excellent outcomes for your business.
    dedicated ai ml experts

    Dedicated AI/ML Experts

    We have a dedicated team of highly qualified and experienced AI/ML developers who are proficient in driving your business growth by 83%.
    design analysis planning and strategy

    Design, Analysis, Planning & Strategy

    Our AI solutions company carefully analyze all the project details from scratch & provides a detailed report at every stage of development process.
    rapid buildup

    Rapid Buildup

    The AI/ML company believe in delivering projects before deadline and that’s why our clients choose to work with us. We never compromise with quality and time as we consider your failures as ours.
    adaptable engagement model

    Adaptable Engagement Model

    We believe in providing 100% satisfaction to our customers so we adopt customized service model to fulfill our client requirements. Our services are fully flexible as we offer you the ability to hire us for full-time, part-time, and even on an hourly basis.
    Confidentiality

    Confidentiality

    Being the best AI/ML software development company, we at BigOh place our clients at the top of the funnel . We keep you safe as we worry about your security.

    Leading AI & ML Development Company Near You

    We are a leading AI/ML development company that helps transform a diverse range of industries such as education, fintech, e-commerce, etc. 

    AI & ML Software Development Process

    AI/ML Software Development process

    Choose from Our competitive engagement Models

    We Help Businesses Achieve Their Goals Faster Through Our AI/ML Services

    Monthly Annual (Save 25%)

    Part-Time

    Min 80 hours per Month 

    Min 2 months contract

    Contact Us

    Full-Time

    Min 3 months contract 

    7 days Lead time

    Contact Us

    Technologies We Use in AI & ML Software Development

    • Technologies
    • Tools
    Scikit Learn

    Scikit Learn

    Tensorflow

    TensorFlow

    Keras

    Keras

    PyTorch

    PyTorch

    NumPy

    NumPy

    Pandas

    Pandas

    Deep learning

    Deep Learning

    ML Flow

    ML Flow

    Jupyter

    Jupyter

    Visual studio code

    Visual studio code

    Pycharm

    Pycharm

    Client Success Stories

    Take a Look at Our Achievements

    AI ML Case Study

    AI ML Case Study

    The client was seeking an application for iOS and Android platforms that would allow users to follow….

    AI/ML Case Study

    AI ML Project

    BigOhTech developed a product to capture the sentiments of the Users and provide insights to the Business owner on…

    Artificial Intelligence & Machine Learning Development FAQS

    What are some of the previous AI and ML use cases you've worked on?

    We have worked on that are following use cases:

    • Sentiment analysis
    • Email Spam detector
    • Topic segregation
    • Image classification
    • Dynamic price prediction
    Can you assist me in developing a SAAS model for AI ML that is similar to Chatgpt?

    Yes, we can assist you with developing a SAAS model for AI ML that is similar to Chatgpt. We can provide you with a customized solution that will include a feature set tailored to your specific needs, as well as a secure, scalable, and robust infrastructure to support the model. We can also help you develop the necessary APIs to integrate the model with your existing applications. Additionally, we can provide ongoing support and maintenance to ensure you have a reliable and successful SAAS model.

    We have an experienced team of AI ML experts who can assist you in creating the required model. In order to get started, we would need to understand your requirements and business goals in detail. Once we have a better understanding of your project, we can create a custom solution tailored to your needs.

    Can you provide a detailed project timeline and budget for the AI ML project app?

    It depends on what kind of  business requirement we have.

    For example:

    Project Timeline:

    1. Project Initiation & Planning: 2 Weeks 
    2. Business Requirements Analysis & Design: 4 Weeks 
    3. AI Model Development: 4 Weeks 
    4. System Integration & Testing: 4 Weeks 
    5. User Acceptance Testing & Deployment: 2 Weeks 
    6. Post-Deployment Support & Maintenance: Ongoing Project

    Budget: 

    1. Project Initiation & Planning: $2,000 
    2. Business Requirements Analysis & Design: $5,000 
    3. AI Model Development: $10,000 
    4. System Integration & Testing: $7,000 
    5. User Acceptance Testing & Deployment: $3,000 
    6. Post-Deployment Support & Maintenance: $2,000/month
    How can AI and machine learning be integrated into existing enterprise solutions?

    AI and machine learning can be integrated into existing enterprise solutions in a variety of ways. For example, AI and machine learning can be used for predictive analytics to anticipate customer needs, identify patterns in customer data, and recommend products and services. AI and machine learning can also be used to automate processes such as customer service inquiries, data analysis, and fraud detection.

    Additionally, AI and machine learning can be used to generate insights from large datasets, enabling businesses to make more informed decisions.

    Finally, AI and machine learning can be used to create more personalized customer experiences, allowing businesses to better target their products and services to their customers.

    How can I ensure the privacy, security and ethical use of AI ML in the enterprise solution?

    In order to ensure the privacy, security and ethical use of AI ML in the enterprise solution, there are a few steps that need to be taken.

    First, it is important to ensure that the data used to train the models is secure and protected. This includes implementing access control systems to prevent unauthorized access, encrypting data to protect it from potential breaches, and using data masking to ensure sensitive data is not exposed.

    Second, it is important to ensure that the AI ML models are operating within ethical guidelines. This includes developing a governance framework to ensure compliance with regulations and ethical standards, as well as monitoring the models to ensure they are not making biased decisions.

    Third, it is important to ensure that the AI ML models are performing as expected. This includes testing the models to ensure they are accurate and reliable, as well as monitoring their performance to ensure they are working correctly.

    By taking these steps, companies can ensure the privacy, security and ethical use of AI ML in their enterprise solutions.

    What are the requirements for implementing AI and machine learning solutions at scale?
    1. High Performance Computing: Implementing AI and machine learning solutions at scale requires powerful hardware and computing infrastructure. This can range from cloud-based clusters of GPU instances to on-premise supercomputers.

     

    1. Data: The success of AI and machine learning solutions depends on having access to high-quality data. It’s important to have enough data to train models and to have data that is representative of the real-world scenarios that the models will be used in.

     

    1. Automation: Automation is essential for scaling AI and machine learning solutions. Automation can reduce the time it takes to train and deploy models, as well as reduce the complexity of the underlying infrastructure.

     

    1. Platforms: Companies should consider investing in platforms that make it easier to deploy and manage AI and machine learning solutions at scale. These platforms can provide the necessary infrastructure, automation, and monitoring capabilities.

     

    1. Expertise: Implementing AI and machine learning solutions at scale requires experts who understand the technologies and can develop, deploy, and maintain them. Companies should invest in recruitment and training to ensure they have the right expertise on their teams.

     

    How do you effectively build, train, and maintain AI and ML models?

    Building, training, and maintaining AI and ML models requires a comprehensive and well-structured approach. In order to ensure the successful development of AI and ML models, the following steps need to be taken:

    • Data collection: Collecting and organizing large datasets to use for training the models.
    • Feature engineering: Engineering features from the datasets to ensure the models are accurate and reliable.
    • Model selection: Selecting the right model for the task at hand.
    • Model training: Training the model using the datasets.
    • Model validation: Validating the model to ensure it is performing as expected.
    • Model deployment: Deploying the model in a production environment.
    • Model monitoring: Monitoring the performance of the model to ensure it is working correctly.
    • Model maintenance: Maintaining the model by updating it with new data and features.

    By taking these steps, you can ensure the successful development, training, and maintenance of AI and ML models.

    What are the best practices for deploying AI and machine learning models in production?
    1. Automate model deployment and monitoring: Automate the process of deploying and monitoring models to ensure that they can be quickly and reliably deployed and monitored in production.

     

    1. Test and validate models: Use rigorous testing and validation techniques to ensure that models are performing as expected in production.

     

    1. Track model performance: Establish processes for tracking and monitoring model performance in production.

     

    1. Deploy models with safeguards: Deploy models with appropriate safeguards in place to ensure that they are not abused or exploited in unintended ways.

     

    1. Adopt a DevOps approach: Adopt a DevOps approach to ensure that models are updated and maintained on a regular basis.

     

    1. Leverage model management tools: Use model management tools to manage and monitor models in production.

     

    1. Use security and privacy protocols: Implement security and privacy protocols to ensure that sensitive data is protected when models are deployed in production.
    How do I assess the performance and correctness of an AI ML solution? Talk about incomplete modeling data or biased data

    Assessing the performance and correctness of an AI ML solution is essential for ensuring its success. However, it can be challenging to accurately assess the performance and correctness of a solution, as there are many potential issues that can arise. Two of the most common issues are incomplete modeling data and biased data.

    Incomplete modeling data occurs when the data used to train the model is missing important information. This can lead to inaccurate results and poor performance. To avoid this issue, it is important to ensure that the data used to train the model is complete and contains all the necessary information.

    Biased data occurs when the data used to train the model is biased towards certain groups or outcomes. This can lead to inaccurate results which are not reflective of the real-world. To avoid this issue, it is important to ensure that the data used to train the model is unbiased and does not favor any particular group or outcome.

    By taking these steps, you can ensure the accurate assessment of the performance and correctness of an AI ML solution.

    How much does it cost to develop an AI or ML Software?

    To obtain a tailored cost estimation for your AI/ML software, simply contact us. Describe your requirements, including project goals, desired functionalities, and preferred platforms. Our experts will analyze your needs and provide a comprehensive cost breakdown, ensuring transparency and informed decision-making.