“twigbit's agile approach and expertise in data science and engineering enabled us to test supply-chain optimisations with our clients quickly and effectively.”
Andreas Rennet, Head of Innovation at A2Mac1Client
A2Mac1, a global leader in automotive benchmarking and innovation.
Objective
The innovation and R&D branch of A2Mac1 wanted to show their clients how AI could turn the raw component and sourcing data on their platform into concrete, lower-cost supply chains. The goal was to prove — in a focused proof-of-concept — that AI-driven optimisation could surface savings their clients could act on.
What we built
twigbit partnered with A2Mac1 across two phases:
Concept phase
- Interviewed stakeholders across the organisation to align on goals
- Ran workshops to define requirements and explore where AI could add the most value
- Designed and tested a UX prototype to validate the concept and its usability
Implementation phase
- Built a visual AI tool on React, Next.js and Mapbox that models supply chains on a live map and recommends optimisations
- Layered AI optimisation over real platform data — the tool weighs sourcing, routing and supplier options and proposes the lowest-cost configuration for each scenario
- Let A2Mac1's clients run "what-if" scenarios agentically: change a constraint and the tool re-optimises the chain and re-estimates the cost impact on the spot
- Worked in agile cycles with fast feedback loops alongside the in-house engineering team
Results
- 27% cost-savings potential identified across the supply chains analysed in the proof-of-concept
- Delivered a fully functional, AI-powered web application within six months
- Gave A2Mac1 a platform to demonstrate data-driven supply-chain optimisation on their clients' real data
- Combined AI and data-science expertise with software engineering and rapid, agile feedback cycles