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Home • AI&ML Services • MLOps Engineering
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Overview
Overview
At Zymr, we help you navigate every stage of your MLOps journey with expertise and precision. From designing a scalable roadmap to optimizing your ML workflows, we ensure smooth, efficient integration into your existing operations. Our MLOps services focus on maintaining regulatory compliance, enhancing security, and driving performance across your models. We deploy flexible solutions that streamline the lifecycle of your machine learning systems, enabling your business to scale and innovate with confidence. Trust our experts to make your ML initiatives seamless, secure, and impactful.
40%
Costs optimized with AI-driven decision-making
60+
Quality programs with QA Automation
50%
Higher productivity with streamlined ML models
30%
AI-accelerated go-to-market
Services
Our MLOps Services
As an experienced MLOps services company, we understand that your ML ambitions can be motivated by various needs. Therefore, our MLOps services help you with these specific needs, whether business needs like faster time-to-market or more specific technical needs like automating CI/CD pipelines for ML.
MLOps Advisory and Strategy
ML Implementation Services
ML Managed Services
CI/CD for ML
ML Observability and Monitoring
MLOps as a Service
MLOps Development Services
Security & Governance for MLOps
Industries
Industries we Serve
Healthcare
- Diagnostics assistance
- Clinical decision support
- Patient monitoring systems
- HIPAA compliance support
Retail
- Personalization strategy
- Sales forecasting
- E-commerce recommendation engine
- Data-driven promotional strategies
Cybersecurity
- Threat intelligence
- Vulnerability management
- Endpoint protection
- Cloud workflow protection
Client impact
AI/ML Promotions Platform Engineering
The client is a New York-based decision science and data management solutions company that offers insights and intelligent platforms for retail establishments. The company has helped many retail customers by empowering them with actionable customer-centric insights for effective decision-making.
Why zymr
Why Partner with Us for MLOps?
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We help design and implement automated pipelines for the entire ML lifecycle.
We help build MLOps solutions that leverage containerized architecture and cloud-native tools.
Our MLOps services adhere to stringent security and compliance standards.
We help integrate CI/CD pipelines tailored for ML to automate testing, version control, and data management.
Path to success
How We Work
Step 1
Engaging with your teams to gain a deep understanding of your business goals, challenges, and current ML workflows.
Step 2
Defining the infrastructure, tools, and processes required to automate a scalable and collaborative ML lifecycle.
Step 3
Implementing customized pipelines for model training, testing, deployment, and monitoring.
Step 4
Automating processes like data preprocessing, hyperparameter tuning, and model retraining.
Step 5
Setting up observability frameworks to track model performance in real-timereal time and flag anomalies.
Tools
TOOLS
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FAQ
FAQs
Why should I consider MLOps for my business?
MLOps offers a set of practices that combine machine learning, DevOps, and data engineering. It will help you automate deployment, monitoring, and management of machine learning models for your business. You can also scale your ML models efficiently while reducing operational risks in your ML implementation.
Can MLOps benefit my team’s productivity?
Absolutely. MLOps automates many manual tasks associated with model training, deployment, and monitoring. This reduces bottlenecks, minimizes human error, and empowers data scientists and engineers to focus on higher-value work.
What are the security implications of MLOps?
Security is at the core of our MLOps practice. We help you implement best-in-class security tools such as HashiCorp Vault, AWS KMS, and Azure Security Center. We also ensure compliance with standards like GDPR and SOC 2. With our MLOps services, you enhance your continuous security testing, vulnerability scans, and access control mechanisms.
Can MLOps work with legacy systems?
It definitely can. We can help develop MLOps solutions that will integrate seamlessly with both modern cloud-based platforms and legacy on-premise systems. Moreover, using flexible integration tools like Apache Kafka, Airflow, and Docker, we will also future-proof your ML workflows.
Let's Connect
Free 2-Week AI Transformation PoV
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Jay Kumbhani
AVP of Software Engineering, Zymr
With over 15 years of experience in AI-driven solutions, we empower businesses to unlock the full potential of their data. Our expertise spans AI/ML model development, data analytics, and automation to deliver intelligent, scalable, and secure applications.
Executive leadership
Technology expertise
Automation expertise
Test automation process
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