Microsoft
Azure AI Engineer Associate
AI-102
About
A small lab for production ML.
We are engineers who would rather talk about your process than our stack. We put models into the workflow that already spends the money, agree the metric before training, and keep serving, monitoring and rollback in the same delivery.
- 8+
- Years in production ML
- 15+
- Production systems
- 5M+
- Predictions / day
- 4
- Countries
SwankyForge is a small engineering team. We publish the before and after numbers for every project on this site, we price with a public calculator that uses the same rates we would quote you, and we hold cloud engineering credentials from Microsoft, AWS, Google and Databricks. We are the right call when something costs too much or takes too long, and the wrong one when you need a demo for a board meeting.
How we work
We start with your problem, not our stack.
Most ML projects die of a communication failure, not a modelling failure. These are the working habits we hold ourselves to, and you can hold us to them too.
The first call is a conversation, not a demo.
We want the process that already spends the money, who touches it, and what breaks when it gets the answer wrong. No slides until we understand that.
One named engineer, start to finish.
The person who scoped your project is the person who ships it and the person who answers when it pages. No account-manager relay, no handover to a junior after signature.
We will tell you not to buy ML.
If a rules engine, a fixed report or better data entry moves your number more cheaply, we write that down and say so. It costs us a project and saves you two quarters.
Transparency is the default setting.
A metric registered before training starts. A written update every week, whether the news is good or not. The repository in your org from day one — nothing lives on our laptops.
Every technical decision gets a plain-language version.
Your CFO should be able to challenge our architecture without a translator in the room. If we cannot explain a trade-off in a paragraph, we do not understand it well enough yet.
We stay after launch.
Serving, monitoring, drift alerts and a rollback path ship in the same delivery as the model. A system nobody can roll back is not finished.
Credentials
Vendor badges we hold.
In progress means the exam is booked.
Microsoft
Azure Data Scientist Associate
DP-100
Microsoft
Azure AI Fundamentals
AI-900
Microsoft
Azure Data Engineer Associate
DP-203
AWS
Machine Learning Specialty
MLS-C01
Databricks
Machine Learning Professional
DB-MLP
Databricks
Data Engineer Associate
DB-DEA
Google Cloud
Professional ML Engineer
GCP-PMLE
Google Cloud
Professional Data Engineer
GCP-PDE
TensorFlow Developer Certificate
TF-DEV
NVIDIA
DLI Fundamentals of Deep Learning
DLI-FDL
CNCF
Certified Kubernetes Administrator
CKA
Got a cost line to move?
Answer six questions and we will tell you what we would actually do — including when the answer is that you do not need us yet.