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Efficient manufacturing for emerging markets
Manufacturing companies in Mexico operate on average under 81.5% of the factory capacity. Costing companies millions of dollars annually.
With 30% of China’s manufacturing capacity expected to move elsewhere, Latin America must implement new technologies to compete with companies flooding the region and increase efficiency to reach demand.
Let's dive in.
You recently took a new job as head of manufacturing operations.
In the first days, you realize the plant's capacity is at a mere 70%, resulting in a significant loss of money and products.
As you dig deeper to figure out the problems, you begin searching for solutions.
Monitoring companies are on the table, but you're also after something to aid decision-making.
You remember that in your last company, Allie was implemented, which made operations smoother and the factory reach their capacity target.
Explain it like I'm five
Allie is a B2B AI-based technology platform for the manufacturing industry.
Hardware: Their team installs “Allie Gateway” hardware to factory machines containing their code, allowing information to flow throughout their platform and creating actionable insights for operators and supervisors.
Platform: They provide real-time advanced analytics of all production lines, allowing supervisors to detect problems in efficiency, product waste, and costs across different stations. Advanced modeling uncovers patterns, anomalies, and data sets.
Allie assistant: Leveraging the factory production data, manuals, and processes, they also offer an AI chat assistant to provide analysis through generative AI.
Founders aim to transform legacy manufacturing companies, starting with Latin America.
Industries: Machine Learning, Manufacturing, AI
Headquarters: Mexico City, Mexico
Year Operations Started: 2022
Team Size: 35 full-time employees and 50 part-time implementation partners
Raised: Pre-Seed $2.3M
Business Model: SaaS, Hardware
What we like:
Scaleable: Allie is going after manufacturing leaders in Latin America. The software is trained by modeling over 125,000 machine variables across manufacturing companies in the United States, Mexico, Spain, Chile, and Colombia, manufacturing products worth around USD $30 billion in annual production.
Network effects: As more companies implement Allie into their operations, the intelligence of their machine-learning models gets smarter. Ultimately making their solution more valuable for each of their clients.
Actionable: Most solutions available in the market don´t learn from the data they provide. Allie leverages the information from production lines and, with the help of Artificial intelligence, transforms data into implementable actions across the production floor.
Efficiency: By anticipating when machines need maintenance or adjustments, operations become more agile, increase efficiency, and save time. Founders claim that companies that have integrated Allie into their operations have boosted efficiency by 10-15%.
Capital: Raising money for a startup is hard enough. However, according to the founder, a major challenge is raising money for a “hardware” enabled company since it's considered a more traditional and capital-intensive model.
Resistance to change: Operation managers in manufacturing companies have their own way of solving processes and finding solutions. They have their protocols, procedures, and methods. Changing an operator's method is very difficult if someone has been doing the same processes for 5,10, or even 20 years, and most operators may resist adopting new methods.
Solution failure: According to research conducted by McKinsey, approximately 70% of digital transformations in the industrial sector ultimately fail. Some contributing factors include a lack of conviction from the CEO or management team regarding the importance of the change, which often results in organizational resistance. Employees may be reluctant to invest additional time in learning new procedures, or the business may lack the necessary capabilities to drive the transformation forward.
Alex Sandoval, Co-founder & CEO, Previously @ Rappi.
Nicolas DeGiorgis, Co-founder & CTO, Previously @ Rappi.
Request intro with founders by sending an email to firstname.lastname@example.org
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