ML Integration Services

Codiste is a specialist in ML integrating progressive machine learning technology into your current systems and processes. Our expert engineers promises that artificial intelligence technology will enhance your operations, enabling you to make wiser choices, show new information, and take action in the moment's data-driven society.

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ML Integration Services
  • Bot Cast AI
  • BonFire - Bonfire Real-Estate Fractionalized Marketplace
  • Mesmr
  • CounterTen - Digital Collectible platform for Loyalty, Brands and events
  • Holygrails - Solana NFT Marketplace
  • Apollo - Apollo Crypto Launchpad
  • CoinXpad - Coinxpad Decentralised Crypto Launchpad
  • Cypha - Make your Music using Cypha app
  • DiveWallet - Decentralised Safest Crypto and digital assets wallet
  • FTWDao - Diversifying the venture investing ecosystem
  • Ikaris - NFT Showcase Mobile App
  • Medizen - Pill Reminder and Drug interaction Detection app
  • MLEstimation - AI Tool to Analyse your Building material
  • NearPro - Connecting Homeowner and top Contractor
  • Bloqhodler - Hedge fund investment app
  • Galaxy Coin - Governance Token & Stacking Defi app
  • zo
  • BrainPulses
  • NextGen

Our ML Integration Services

Augment your team with our Blockchain experts for ML Integration services to turn your dream project into reality.

Why Codiste for ML Integration Service?

We bring innovation with ML Integration. Our services with machine learning deliver experience with quality, transparency and with proper communication.

Comprehensive Development

Expertise in Seamless Integration

We have a proven track record of integrating Machine Learning (ML) technologies into ecosystems. Our team is skilled in utilising APIs, microservices and containerization to ensure an effortless connection. Incorporating ML into your existing infrastructure we maximise its potential. Enhance its capabilities.

Comprehensive Development

Mastering Data Preprocessing

Data is the foundation of ML. Your data will be cleaned, converted, and formatted for the best model performance thanks to our data preprocessing mastery. We address issues like missing values, outliers, and feature scaling, laying the groundwork for precise forecasts and useful insights.

Comprehensive Development

Model Performance and Monitoring

In addition to integration, we also excel in these areas. Our solution's extensive performance metrics and real-time monitoring can monitor model correctness, spot abnormalities, and get prompt insights for any adjustments that might be required to ensure the long-term success of your ML deployment.

Comprehensive Development

Varied Domain Knowledge

We excel in many different industries. We deliver extensive domain expertise that matches ML solutions with particular sector peculiarities across industries including banking, healthcare, manufacturing, and e-commerce. This will assure you that the integrated models will succeed technically and strategically in line with your corporate objectives.

Comprehensive Development

Governance & Compliance Assurance

Data ethics and legal compliance are our top priorities. Our Governance and Compliance Assurance includes explainability methodologies, model documentation, and version control. We guarantee your ML integration is both responsible and effective by adhering to industry standards and laws like GDPR and HIPAA.

Comprehensive Development

Collaboration-Based Partnership

Not only do we provide solutions, but we also create Collaborative Partnerships. Understanding your particular needs, coordinating with your objectives, and keeping you updated along the integration path are all part of our collaboration. Our experience is complemented by your team's, resulting in a positive synergy that promotes success and innovation.

Our Machine Learning Consulting Approach

We assist organizations in a seamless journey of utilizing AI-driven insights, from defining clear business goals to implementing and monitoring ML models.

1

Business Goal

Understanding the desired result, establishing key performance indicators (KPIs), and coordinating the ML strategy. With the larger corporate objectives are necessary for this.

2

ML Problem Framing

Convert the business objective into a clear-cut machine learning challenge. In this phase, the type of ML task (such as classification, regression, clustering) is determined, the relevant evaluation metrics are chosen.

3

Data Processing

Preparing and preprocessing the data will assure its accuracy, completeness, and suitability for ML and AI algorithms. This covers operations like feature engineering, addressing missing values, data cleansing, and converting data into a format for model training.

4

Model development

Using the cleaned-up data, create, train, and fine-tune the machine learning model. Choosing the right algorithms, optimizing hyperparameters, and assessing model performance using methods like cross-validation comes in this stage.

5

Deployment

To make the trained ML model available for real-time predictions, integrate it into a production environment or application. This entails creating a deployment architecture, managing model versioning, and setting up data pipelines for seamless integration.

6

Monitoring

Monitoring important metrics, identifying and dealing with model or concept drift, and putting in place safeguards to guarantee the model's dependability and efficiency over time.

Hire our ML Experts to minimise Application Integration complexities

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Technology Stack

Our experienced team of engineers pack yourMachine Learning Consulting with the best technologies ensuring that enable fault-free operations and be ready for transforming and scaling business.

  • pytorch

    pytorch

  • Scikit_learn

    Scikit Learn

  • Apache_Spark_

    Apache Spark

  • Pandas

    Pandas

  • github

    github

  • bitbucket

    bitbucket

  • git

    git

  • kubernetes

    kubernetes

  • docker

    docker

  • Power-BI

    Power-BI

  • Tableau

    Tableau

  • Matplotlib

    Matplotlib

  • Airflow

    Apache airflow

  • sagemaker

    sagemaker

  • Autokeras

    Autokeras

Industries We Serve

Being a trusted Machine Learning Consultant, we have worked with a wide range of sectors on a global scale and have been a part of their growth stories.

Insurance

Insurance

Real Estate

Real Estate

Event Industry

Event Industry

Healthcare

Healthcare

Fintech

Fintech

Renewable & green energy

Renewable & green energy

Sports Tech

Sports Tech

Gaming

Gaming

E-Commerce

E-Commerce

Funded Start-ups

Funded Start-ups

Cleantech Space

Cleantech Space

Human Resources

Human Resources

Our Engagement Models

01

Fixed Engagement Model

Get a predefined budget and timetable that is tailored for machine learning solutions projects with well defined scope and needs. This strategy, which is best for small to medium projects, guarantees cost predictability and provides the stated deliverables within the scheduled time range.

02

Time and Material Engagement Model

Our Time and Material Engagement Model is flexible and adaptable, making it ideal for machine learning professional services projects with changing requirements and undefined scope. As a result, there is more flexibility in adapting changes, scalability, and continued cooperation throughout the development lifecycle because you only pay machine learning consultant hourly rate actually used on the project.

03

Hire Dedicated Team Model

Strengthen your internal resources by putting together a group of talented ML Consultants and engineers that are only committed to the success of your project. This model offers the benefit of an extended development team that works extremely collaboratively to meet the needs and goals of your organization while guaranteeing smooth communication, control, and transparency.

FAQs

Machine Learning (ML) integration is about deploying the ML models into the existing systems or databases of a business. Businesses can enhance data processing operations with ML integration. Improving customer servicing operations, automating business processes, and making insightful business decisions become easy for businesses with the ML integration. Also, the accuracy rate of business data improves a lot by the deployment of ML Models.

Integrating Machine learning (ML) with Android apps has become quite common among businesses from all verticals to enhance their business operations. The integration process can be easily done with the below-given tools and frameworks along with hiring an expert ML developer.
  • TensorFlow Lite
  • ML Kit
  • PyTorch Mobile
  • Caffe2
  • Scikit-learn

Integrating two businesses through a merger of takeover can be performed based on their nature of operation and the kind of activities they involved. Those two factors determine what type of integration suits better for merging.
Here are the lists of 4 common Integration types widely used by businesses across the world to merge with others.
  • Horizontal Integration
  • Vertical Backward Integration
  • Vertical Forward Integration
  • Conglomerate Integration

As personalization becomes inevitable for businesses, developers integrate Machine Learning (ML) to business websites or web applications to achieve better user experience. Integration ML into web requires appropriate web framework, essential infrastructure, and a perfect ML model for integrating with website/web apps.
Here are the lists of top 3 commonly used ML frameworks by the developers to deploy ML Models on Web platforms.
  • TensorFlow
  • PyTorch
  • Scikit-learn

Ready to supercharge your systems with seamless machine learning integration?

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Case Study

ML Estimation

Streamline HVAC project bidding with ML estimation, automating drawing annotation and generating accurate bill of materials. Save time, differentiate yourself in the industry, and leverage innovative technology for detailed quantity take-offs.

MLEstimation - AI Tool to Analyse your Building material

Satisfied clients is our proof of our excellence!

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