End to end

A One-Stop Partner For Your Whole Journey

We accompany and support clients throughout the whole process of AI development.

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Understanding Client Needs
We study the case to understand clients needs and how AI can help with their problem.
Data Gathering
Data usually comes from different sources and needs to be standardized and filtered based on quality and other criteria.
Data Tagging
In most cases, ML is not only about data but tagged data. At this stage, we define how to tag and identify the data, choose the best tool to do it, and we tag it.
Model Training
We search for the model that suits best the specific case and its characteristics.
Be it on cloud or edge solution, we pack the model and software code around it and leave it production-ready.
Analyze Results
Once the solution is in use, we monitor its performance and impact on the business to see where the focus should be placed on the next iteration.
Sprint-Based Iterations
We Split the Development Roadmap Into Sprints
On each sprint, we define a high level goal, and how that goal translates into a metric.
Then tasks are set to achieve the goal and at the end of the sprint we make sure it is reached.
We Believe That a Steady Way Of Constant Improvements Is The Way To Achieve Success.
Sprint 12
Sprint 13
Sprint 14
Sprint 13
Make self-checkout faster
Train lighter model
Optimize with TensorRT
Current State
Scan takes 1 second per product
Scan needs to take 0.5 seconds per product
Scan now takes 0.3 seconds per product
Ground-Based Expectations
At The End Of The Day, It’s The Business Impact What Matters
We work together with you to understand how to measure this impact, and keep track of it during the development process.
That way, we ensure that improvement in ML metrics like precision and recall translate into KPI improvement too.
How we helped an entrepreneur build a prototype and advance on fundraising
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