Reasons Why You Need MLOps

Deployment Challenges

Lack of version control, reproducibility, and standardization lead to errors, inconsistencies and operational inefficiencies, impacting model reliability and performance.

Monitoring Challenges

Due to the constant changes in model behavior and the complex model lifecycle nature can lead to model drift, resulting in degraded model performance and incorrect predictions.

Model Governance Challenges

Complex governance frameworks can create barriers to effective model governance while model visibility and explainability issues can limit model transparency and accountability, leading to concerns around model bias and fairness.

Model Security Challenges

Lack of model security leads to model malfunction, data poisoning, model theft and evasion; resulting in model tampering, incorrect predictions and potentially significant business impact.

Streamline your Machine Learning projects with Blackstraw MLOps as a service

Did you know that only 1 out of 10 data science projects end up delivering value to organizations as 90 percent of machine learning models fail to make it to production. This is due to the ever-evolving data, which requires continuous monitoring, training, and redeployments. As a result, bringing ML models to production can be challenging and time-consuming process that requires the discipline of delivering models through repeatable and efficient workflows known as machine learning operations (MLOps).

With Blackstraw, you can avoid the expense and effort for developing and maintaining your Machine Learning models. Our team of data experts has developed proprietary MLOps frameworks and approaches, which can be tailored to fit seamlessly into your existing ecosystem; allowing you to reduce the time-to-deployment, minimize risks and improve operational performance.

Business Benefits

Accelerated Innovation & Growth

Faster time to deployment and iteration of ML models results in a shorter time to market, allowing businesses to innovate and grow at a faster pace.

Boost Business Decisions with Reliable Model Reproducibility

Achieve greater transparency, reliability, and accountability in machine learning processes through model reproducibility.

Efficient Management of Data and Model Drift

Quickly monitor and manage data and model drift for operationalized models ensures that models remain relevant and performant, resulting in optimized business outcomes.

Blackstraw’s MLOps as a service offerings

MLOps Consulting

  • ML Strategy & Roadmap
  • ML Technology Services and platform selection
  • Data strategy for MLOps

MLOps Implementation

  • Standardized data and model pipelines
  • Data and model security inclusive deployments
  • Scalable model serving

MLOps Support

  • Model Monitoring and Governance Support
  • Cloud and DevOps support for the model platform

Our Technology Expertise

Why Blackstraw

End-to-End AI &
Automation Solutions

Blackstraw is an AI & Automation solutions company that offers end-to-end services, from data engineering to MLOps, with deep expertise in AI/ML, Data Science implementations.

ML-led Operations Expertise Automation Solutions

Our team possesses in-depth knowledge and expertise in ML libraries, ML platforms, and MLOps frameworks that are on par with global standards, enabling us to deliver powerful ML-led operations.

Cutting-edge Innovation

We focus on implementing the latest technology stack with speed, reliability, and quality, ensuring that our approach and frameworks are cutting-edge and innovative.

Delivery Excellence

Our thorough understanding of the MLOps life cycle enables us to effectively collaborate with data scientists, business analysts, and data SMEs, ensuring delivery excellence for our clients.

Don’t let the challenges of
machine learning
management slow down your
innovation and growth