Production Deployment
After evaluating the MVP and getting feedback from real users, we move on to production, focusing on the use in a real context with the highest security. You can perform this service independently. We adapt to you and to the moment of your project.
Benefits
We guarantee a robust and future-proof solution thanks to our experience in ML operationalisation.
Full system integration
We integrate the system into a real-world environment by solving the challenges of security and compatibility with existing systems.
Useful throughout the entire lifecycle
We keep the solution up to date so that it remains useful through detailed long-term service management.
“The research profile of Sciling’s staff impressed me and gave me confidence that they would figure out how to make this project a big success no matter what obstacles we might come across.”
Asher FergussonAsher & Lyric
In Depth: Production Deployment
After testing the MVP with the fundamental characteristics of the solution and obtaining evidence of its results, we develop the complete project. This development focuses on its implementation and real use, as well as its scalability, ensuring that the solution can grow and adapt to future needs.
Methodology
1. Development
Our team of PhDs and developers carry out the solution based on the previous data and strategy to meet the objectives.
2. Integration and deployment
The solution is integrated into the organisation’s existing systems and technologies for immediate operation.
3. Evaluation and follow-up
We evaluate the results of the solution and continue to work together to ensure quality and support for the solution.
You are ready for production deployment if you...
You have validated your idea and solved the technological risk.
You have guarantees about the market acceptance of your solution.
Your project is viable at a business level.
‘The key to moving from a PoC to a production system is to avoid mismanaging expectations.’
Adriana Gallego (Value Generation Leader, Sciling) in ‘Interfaces de Futuro’.
Success Story: Asher & Lyric
Asher and Lyric Fergusson are two travel bloggers and researchers. Their goal was to analyse user reviews of Aribnb and Uber to discover the most frequent problems and the degree of safety.
Given the large volume of data to process, they decided to rely on Sciling to automate the task using AI and NLP. After four iterations, a programme was obtained that extracts the most frequent problems based on the analysis of tweets and is kept updated and refined with each iteration.
420
Airbnb tweets analysed
1,8
Uber tweets analysed
78
precision
Ensuring the success of your AI project
75% of AI projects fail due to a bad approach or not having an expert team.
At Sciling we have 10 years of experience in developing AI projects. If you have already identified your organisation’s challenge or the use cases that could use AI to be solved, contact us so we can help you.
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