MLOps Company Blackthorn AI: Expert Services for Your ML Needs
MLOps services eliminate manual toil and mistakes when handling multiple versions of data preprocessing and feature engineering pipelines. They also manage datasets, respective train/validation/inference source code, and models by automation and high-level orchestration.
50 +
Projects
400 +
Publications
MLOps Engineering Services
Our MLOps managed services focus on eliminating manual effort and reducing risks across machine learning operations. We automate workflows, manage deployments, and connect pipelines to help businesses save time and stay consistent in their ML practices.
Domain Expertise We Bring
With deep AI & ML expertise, we address industry-specific challenges through reliable, fast solutions. Having worked extensively in these industries, we speak your language, understanding unique needs and delivering value-driven MLOps services focused on your domain.
About Blackthorn AI
Blackthorn AI is an MLOps company with 10+ years of experience and 50+ successful projects to its name. Our goal is to build long-term, win-win partnerships, not sell hours or make empty promises.
Founded by ML architects and MSc or Ph.D. scientists, our team loves solving complex challenges, optimizing neural networks, and achieving top-tier performance.
Our approach is rooted in measurable results, from end-to-end project management to guarantees tied to baseline metrics.
4.2
years average customers engagement
50 +
world-class engineers
10 +
years full-cycle development experience
50 +
AI & Data projects delivered over the last 3 years
Our Awards & Certifications
To deliver excellent MLOps services, we’ve mastered technologies like TensorFlow Extended, Focker, Kubernetes, MLflow, AWS, GCP, DVC, and Azure, among others. But there’s more – our certifications and awards prove that our work leaves no room for mistakes or downtime, ensuring every solution is rock-solid and professional.
Top Artificial Intelligence Company
Clutch, 2024
Cloud Architect
Google Cloud Certified Professional
Top Generative AI Company
Clutch, 2024
Cloud DevOps Engineer
Google Cloud Certified Professional
Top Global AI Company
Clutch, 2024
Cloud Engineer
Google Cloud Certified Professional
Top Computer Vision Company
Clutch, 2024
Solutions Architect
AWS Certified Associate
Top Computer Vision Company
Clutch, 2024
Software Developer
AWS Certified Associate
Clutch Spring Champion
Clutch, 2024
Java SE 8 Programmer
Oracle Certified Professional
Global Company
Clutch, 2023
Java SE 8 Programmer
Oracle Certified Associate
Python Programming
PCAP Certified Associate
TensorFlow Developer
TensorFlow Certified
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What Business Outcomes Delivers Reliable MLOps Engineering
If your team works on multiple DS/AI directions and/or approaches, it will face the chaos of versions of data preprocessing, datasets, features, and models in no time. You will also be surprised to discover that Data Scientists are not as good as you want them to be at infrastructure works.
MLOps engineering services is a long-term investment with the following benefits:
Fast Iterations with Automated Workflows
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We make experiments fast and frustration-free.
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No need to rewrite Python, Java, or R code every time.
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Once workflows for training and validation are set up, you can toggle hyperparameters and automate processes – saving time and energy.
Flexible Scaling for Computational Resources
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High-demand periods don’t have to mean high bills.
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We automate resource scaling to meet your needs without wasting budget.
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From GPUs that shut down automatically to optimized cloud usage, with our MLOps services you’ll only pay for what’s needed.
Consistent Results Tracking
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Experiment tracking shouldn’t depend on memory.
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We log hyperparameters, validation results, and key metrics automatically.
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This creates a clear, reliable history of every experiment – no more guesswork or missed details.
Risk Mitigation and Deployment
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Our MLOps engineers eliminate mistakes by automating deployments, detecting input drift, and comparing new models to old ones.
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With built-in monitoring and feedback loops, your models adapt to real-world conditions without manual intervention.
MLOps Projects Successfully Delivered by Our Team
Explore our MLOps managed services in action. From a Llama3-powered AI agent for HIPAA-compliant medical file retrieval to a Multi-Omics GenAI platform for drug discovery, our projects deliver real impact. See how we’ve transformed industries like healthcare, oil & gas, fintech, and more.
Multi-Omics GenAI Platform
A Framework for Automatic Bundling Machine Learning Microservices
Intelligent Documents Processing
Predicting Readmission Risks
What Clients Say Аbout Our Solutions
“The way Blackthorn AI stepped in and helped us revamp the model was excellent” – With a 5/5 Clutch rating, our clients praise our proactive communication, technical expertise, and commitment to deadlines. Explore how our solutions turn ideas into real results and build trust.
Yoanna Gouchtchina
CEO, Skentechnologies LLC
All our needs were addressed in a very professional manner.
Alejandro Gonzalez
Product manager, Monitoring Life
They always delivered on time and showed 100% transparency in the project development.
Serhii Ivanets
CTO, VAN Group
Thanks to their open management style, they had an exceptional partnership that resulted in success.
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Clients Also Ask
Our MLOps company can help prevent performance degradation by monitoring track technical metrics like CPU usage and performance indicators like accuracy. Feedback from production is recorded and used to detect degradation, triggering updates via retraining or feature adjustments, keeping the model relevant without manual intervention.
MLOps automates data exploration, feature engineering, and hyperparameter tracking. It ensures models are evaluated on real-world approximations, aligning metrics with expectations, and facilitates effortless selection of the best-performing model for deployment.
MLOps services prevent chaos caused by managing multiple versions of preprocessing pipelines, datasets, and models. It automates workflows, helping data scientists avoid infrastructure pitfalls, like setting up Kubernetes, while ensuring consistent and reliable outputs.
Key deliverables include a data warehouse groomed for AI, the best-trained model ready for production, integrated ML services deployed to production, and automated feedback loops for continuous model improvement and performance tracking.
MLOps consulting services can help you automate the scaling and shutting down of computational resources, preventing wasteful spending on idle GPU instances. It ensures resources are available when needed while avoiding unnecessary costs during off-peak hours or forgotten deployments.