MLOps for Computer Vision
Building computer vision products? To go from experimental models to commercial application, you need infrastructure to make your CV model work in real-world setting.
Get MLOps strategy that’s tailored to computer vision.
From model training to continuous monitoring, we build models and their infrastructures that perform well across various deployment environments like cloud, edge or on-prem.
Let’s talk about your computer vision models!
We’re Working With Hardware and Software Vendors and Back Up Computer Vision-Based Projects with MLOps
Vision-Based Solution Manufacturers
Get experts in machine learning and neural networks to help you with infrastructure.
Tech Solutions Companies
Do you lack computer vision expertise? Let’s partner up and ask our engineers to help you with MLOps and Computer Vision.
Hardware & Software Vendors
Integrate computer vision and into your systems and boost your product with intelligence that gives you competitive advantage.
Not Sure What You Need? Book an Audit!
Get an expert who will review and recommend infrastructure tools and approaches. You’ll receive a comprehensive audit report detailing the current state, gaps, and clear next steps for your MLOps journey.
What Does MLOps for Computer Vision Models Mean?
Computer vision models deal with unstructured visual data and require more expertise than typical machine learning models to stay reliable. MLOps provides the infrastructure and automation to manage this complexity. MLOps for CV adapts MLOps services to the unique demands of visual data, and helps maintain computer vision models in production.
Data Management
Get a partner who can support you in data sourcing (and generating synthetic data if needed) as well as image labeling, preprocessing, and helping you build data lakes and warehouses that are tailored to your needs.
Infrastructure Setup
Work with a team that understands the infrastructure demands of computer vision at scale. We’ll help you select and configure the optimal mix of CPUs, GPUs, and cloud services (AWS, Google Cloud, or Azure) that’s custom fit to you.
Continuous Monitoring and Automation
Integrate monitoring and automated alerts to quickly identify data drift, degradation, or anomalies. Plus, streamline repetitive tasks like retraining, evaluation, and deployment to accelerate development cycles without losing accuracy when you’re scaling.
Machine Learning Model Deployment
We can wrap your model in an API, serve your model using cloud services, and set up autoscaling, so it can handle production traffic. We can also integrate your model to apps, pipelines, or edge devices and check latency, throughput, drift.
On-going Support
After deployment, we provide comprehensive support that includes model versioning and rollback mechanisms, as well as automated retraining pipelines that trigger when thresholds are crossed or new labeled data becomes available. We also handle ongoing dataset maintenance, so your model stays relevant.
Not There Yet? Ask Us For Full Computer Vision Solution Development
Let’s build a vision-based solution that performs where you need it the most: on edge devices, in the cloud, or on-premise systems. Partner up with us and get a custom computer vision solution that’s relevant to your task.
Get Support From Idea to Scaling Computer Vision
- Solution ideation through consulting
- Computer vision roadmap
- PoC development
- PoC to commercial development
- Software development
- Ongoing support
Companies Across the World Have Already Trusted Our Team’s Expertise
Organizations worldwide trust us to identify opportunities, support optimization investments, and provide IT infrastructure assessment services tailored to each business’s needs.
Why Should You Hire MLOps Experts from DAC.digital?
Speed Up Time-to-Production with Automated Pipelines
Automatically Monitor Model’s Performance
Optimize Your Infrastructure to Work on Edge
Catch Issues Before They Become Problems
Reduce Manual Effort
Recover From Downtimes Faster
Success Highlights from Our Team
Scalable AI Expansion Support
Guided clients from Proof of Concept through full production scaling, so they could prepare their solution for the next stage of product development.
Read more: Is Your PoC Too Slow? How We Optimized Algorithm Performance for Commercial Development
Model Optimization Excellence
Reduced model sizes by up to 90% using techniques like pruning and quantization, maintaining high accuracy while lowering resource demands.
Up to 80% Savings on GPU Costs
Optimized AI workloads to reduce cloud GPU expenses dramatically. For instance, we achieved 5x reduction for a beauty industry client.
Read more: Fully Automated Manicure Robot Powered by Ultra-Precise Computer Vision
What Our Clients Say About Us?
We’re an Official AWS Partner
Our team is recognized by Amazon Web Services, so if you work with Amazon SageMaker, Glue, Kinesis, we can help you use AWS-native tools to reduce cloud costs, automate more of the ML lifecycle within AWS, and align your MLOps with best practices recommended by AWS Well-Architected Framework.
Book an MLOps for Computer Vision Now
Contact us!
Send us an email: [email protected]