MLOps Consulting
Let our experts assess your ML computing infrastructure. The outcome? An actionable MLOps audit doc that you can act upon immediately.
Get expert consulting that will guide you on how to optimize machine learning infrastructure for the right environment like cloud, edge, or on-prem environments.
Let’s talk about your challenge!
Are You Stuck With?
Your team’s building an ML-based solution, but all the time you get this:
Rising Costs
Security Concerns
No Experiment Tracking
Slow Deployments
Lack of Internal Expertise
Frequent Downtimes
MLOps Consulting Service Can Help You Get Over That!
In 3 steps, we will give you a clear plan of action.
Intro call
We start with a discovery conversation to understand your current challenges and goals.
Assessment
Our team performs a thorough evaluation of your existing ML infrastructure, processes, and workflows.
Recommendations
Based on our findings, we provide tailored, actionable advice to optimize your MLOps practices.
You’ll Get an MLOps Audit as an Outcome.
You’ll receive a comprehensive audit report detailing the current state, gaps, and clear next steps for your MLOps journey.
Ready to Start?
Get on an MLOps Consulting at Every Stage of Model Lifecycle
Facing challenges in building or scaling machine learning projects? Explore how we can consult you at every stage of your AI journey to build reliable, scalable, and cost-effective MLOps workflows tailored to your needs.
For companies at Proof of Concept stage
- Design and build foundational AI/ML infrastructure to replace manual processes
- Implement basic DevOps workflows tailored for AI/ML model lifecycle
- Establish model management practices including versioning and tracking
For companies at R&D or MVP stage
- Set up scalable data and model management systems
- Cost optimization strategies for AI/ML infrastructure
- Implement reproducibility tools
- Create centralized repositories for models and data
For companies ready to scale commercially
- Deploy models to production with automated CI/CD pipelines
- Set up continuous monitoring for model performance and data drift detection
- Automate deployment and rollback processes to minimize downtime
- Optimize infrastructure costs while maintaining high reliability and scalability
Not There Yet? Ask Us For Full Machine Learning Development
Let’s build a production-ready solution that performs where you need it most: on edge devices, in the cloud, or on-premise systems. Partner up with us and get a custom machine learning model that’s relevant to your task.
You Can Count On Us For:
- Model design and training
- Performance evaluation
- Model explainability
- Inference optimization
- Deployment and integration
- Monitoring and governance
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.
Combine ML with DevOps Expertise
Don’t look for DevOps specialists elsewhere. We have them right here on our team. Our DevOps engineers build automated CI/CD pipelines, manage infrastructure as code, and implement monitoring systems for machine learning-based apps.
What Can You Expect from MLOps Consulting?
Our MLOps consulting and audit helps you spot bottlenecks, fix hidden issues, and build a foundation ready for scale. If you’re facing frequent downtimes, delivery delays, or unexpected production failures, we’ll help you regain control.
Planning a major infrastructure change?
We’ll give you a clear roadmap to migrate smoothly, without disrupting your machine learning operations.
Why Should You Book MLOps Consulting with DAC.digital?
Slash Your AI Infrastructure Costs
Run Leaner Models in Production
Handle Traffic Spikes Without Downtime
Catch Issues Before They Reach Users
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 Audit Now
Contact us!
Send us an email: [email protected]