You will get ML Model Deployment on AWS in Weeks not Months or Years
Project details
Our MLOps solutions are designed to cater to startups and enterprises alike, providing a comprehensive and customizable approach to deploying and managing machine learning models on AWS.
♦️ Eliminate ML project delivery risk ♦️
Our use-case specific MLOps strategy consultation, battle-tested AWS infrastructure stack, and pay on success option reduce the risk of project failure to almost zero.
♦️ Get to production in 30 days or less ♦️
80-90% of the required code is already written, tested and well documented. All that’s left to do is adding use-case specifics like model artifacts, and serving code. This can either be done by you, with our guidance, or for you by our team.
♦️ Full repo access - no vendor lock-in ♦️
The code repository will be all yours. Change or add infrastructure, deploy and operate 1000 models, we don’t care. As long as you don’t share the code publicly.
♦️ Tailored Solutions ♦️
Our "Done with you", and "Done for you" offerings will tailor our repository template to your specific use-case, ensuring there's a fit for every organization's needs and capabilities.
Let's talk!
♦️ Eliminate ML project delivery risk ♦️
Our use-case specific MLOps strategy consultation, battle-tested AWS infrastructure stack, and pay on success option reduce the risk of project failure to almost zero.
♦️ Get to production in 30 days or less ♦️
80-90% of the required code is already written, tested and well documented. All that’s left to do is adding use-case specifics like model artifacts, and serving code. This can either be done by you, with our guidance, or for you by our team.
♦️ Full repo access - no vendor lock-in ♦️
The code repository will be all yours. Change or add infrastructure, deploy and operate 1000 models, we don’t care. As long as you don’t share the code publicly.
♦️ Tailored Solutions ♦️
Our "Done with you", and "Done for you" offerings will tailor our repository template to your specific use-case, ensuring there's a fit for every organization's needs and capabilities.
Let's talk!
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$4,000
|
Standard
$17,000
|
Advanced
$39,000
|
|---|---|---|---|
| Delivery Time | 1 day | 30 days | 70 days |
Number of Revisions | 0 | 1 | 3 |
AI Model Integration | - | - | |
Detailed Code Comments | |||
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$5,000
Additional Revision
+$1,500About Sebastian
ML Engineer | AWS | Get AI Productive in Days
Hamburg, Germany - 4:50 pm local time
Bio: My passion is Data Science, MLOps and Cloud Engineering (AWS) and I bring 7+ years of industry experience. Recently I've founded my own MLOps startup, and before that I've worked as a consultant, on over 10 successful customer projects at five different Fortune 500 companies (see LinkedIn).
Offering: I'm here to make your ML deployment happen. Much faster than you would usually expect. I have a repository ready that already contains a battle tested cloud infrastructure stack (as code) together with a selection of pre-configured MLOps tools, Automations and so much more. In addition, I provide in depth video guides that will help you understand my approach to MLOps and AWS and easily onboard new developers or freelancers to your project in the future if needed.
As you can see, my offering is not just a service but also a product that drastically reduces the time to production and hence the overall cost. It also makes your MLOps setup much more future-proof and reliable, and eliminate the usual ML project delivery risk.
Here are the key benefits:
♦️ Eliminate ML project delivery risk ♦️
Our use-case specific MLOps strategy consultation, battle-tested AWS infrastructure stack, and pay on success option reduce the risk of project failure to almost zero.
♦️ Get to production in 30 days or less ♦️
80-90% of the required code is already written, tested and well documented. All that’s left to do is adding use-case specifics like model artifacts, and serving code. This can either be done by you, with our guidance, or for you by our team.
♦️ Full repo access - no vendor lock-in ♦️
The code repository will be all yours. Change or add infrastructure, deploy and operate 1000 models, I don’t care. As long as you don’t share the code publicly.
For more info, visit qops.ai or message me here on Upwork.
Steps for completing your project
After purchasing the project, send requirements so Sebastian can start the project.
Delivery time starts when Sebastian receives requirements from you.
Sebastian works on your project following the steps below.
Revisions may occur after the delivery date.
Use Case Specific MLOps Strategy Consultation
2–3h discovery call where we get to know each other and evaluate if q·ops is the right fit for one of your use-cases (up to 3).
Business Requirements Analysis
We conduct interviews with stakeholders from your company and potentially some end-users, to better understand the use-case, data and business requirements.