Ameba: “Portugal is the Silicon Valley of the Textile Industry”

Textile supply chains are among the most complex in the world, with thousands of SKUs, multiple suppliers, and critical information still scattered across emails, spreadsheets, and PDFs. This fragmentation makes operational visibility and real-time decision-making difficult, making the practical application of Artificial Intelligence one of the greatest opportunities for the sector.

In this context, T Jornal interviewed Cedrik Hoffman, CEO of Ameba, to gain a deeper understanding of how this Artificial Intelligence platform, developed for textile and apparel manufacturers, works, what concrete advantages it brings to the sector, the potential it identifies in the industry, and the prospects for future partnerships with the Portuguese textile and apparel industry. Developed in collaboration with a select group of industrial partners, including the Portuguese companies Anglotex and Carmafil, Ameba uses AI to interpret supply chain data, link it to SKUs, orders, and suppliers, and transform it into a real-time operational view.

How would you describe what Ameba does, briefly?

Ameba is an AI platform built for textile and garment manufacturers to automate and control end-to-end commercial and buying workflows. It pulls information automatically from emails, spreadsheets, PDFs and messages, turns it into structured data, and gives teams a live dashboard showing SKU readiness, critical paths across purchase orders, and early warnings when deliveries are at risk. It can even chase suppliers automatically and sync every data point back into ERP and PLM systems automatically so teams spend less time hunting for updates and more time generating business and building deeper relationships with both customers and suppliers.

What led you to create Ameba?

Ameba came directly from my own experience running a manufacturing business in Asia, and later building the supply chain at VALOREO, one of Latin America’s largest e-commerce groups. At VALOREO, we spent more time finding delays than fixing them – chasing suppliers, updating spreadsheets, and reacting to surprises literally every day.

Even with some of the best supply chain software in the world, the work remained painfully manual. That’s when I realised most tools were built for finance teams first, not for the operators actually running buying and production. That gap became the opportunity: build something purpose-built to cut through the chaos and give supply chain teams speed, clarity, and control again.

Could you share a bit about your professional background and how it influences the way Ameba is managed today?

I’m originally from Germany, and moved to China at 16 as a high-school exchange student, an experience that shaped my entire life. I later studied at London School of Economics and started my career in investment banking at Goldman Sachs and BNP Paribas, before deciding I wanted to build companies rather than just advise them.

Because I speak Mandarin, I moved to Taiwan, acquired a manufacturing business, and scaled it into a Tier 1 hardware supplier for some of the world’s largest gaming companies. During the pandemic, that business went through a very tough period. Around that time, I teamed up with friends from private equity and moved to Mexico to co-found VALOREO, acquiring and scaling high-growth brands across fashion, CPG, and furniture. Within two years, we raised over $160M, acquired 25+ brands, and scaled to 200+ employees across Mexico, Colombia, and Brazil.

Those experiences taught me one thing very clearly: when information is fragmented, execution becomes chaos. That’s why Ameba is built around automation, speed, and operational clarity.

What excites you most about this project?

I’ve lived the problems our customers face, both as a supply chain operator and as the CEO of a manufacturing company, so in many ways, I’m building Ameba for a past version of myself.

Textile supply chains are some of the most complex in the world: thousands of SKUs, endless components, many suppliers, and constant change. That complexity creates messy, fragmented data, and applying AI to that exact problem is, in my view, the biggest opportunity in the entire market. Not because it sounds exciting, but because it’s where AI can deliver the most measurable impact on real businesses.

And on a personal note, my wife is a fabric supplier in Taiwan, so if we do this right, we won’t just improve operations for our customers, we’ll improve life for the whole ecosystem – including suppliers like her.

Ameba aggregates highly fragmented information. How does this work in practice and what types of data are structured on the platform?

Ameba uses AI to interpret supply chain information from emails, spreadsheets, and PDFs, where most operational data still lives today. We extract the key details, connect them to the right SKUs, orders, and suppliers, and turn it into a real-time operational view.

Behind the scenes, we use multi-step AI “agents” that read messages and attachments, interpret the content, map relationships, and take actions like supplier follow-ups or risk alerts. Our goal is to turn messy communication into a clear, explainable source of truth, from sales order all the way through to purchase order and in-house production.

“When information is fragmented, execution turns into chaos. That’s why Ameba is built around automating speed and operational clarity.”

What new features or technological developments are currently being planned or developed?

We’re rolling out two major capabilities:

First, automated tech pack processing: Ameba extracts and translates key product information, specs, measurements, materials, timelines, and syncs it directly into ERP systems. This reduces manual work dramatically and speeds up onboarding of new products.

Second, advanced analytics: real-time KPI dashboards and charts that help teams spot issues earlier, understand performance trends, and make better decisions across commercial and supply chain execution.

How has Ameba evolved since its early days?

In the early days, we built Ameba side-by-side with a small number of partners, including Anglotex and Carmafil. We spent real time on the ground with their teams, understanding the messy reality of how buying and production actually works.

Today, Ameba is a scalable platform with strong integrations, so we can roll out faster across more manufacturers, without losing the user-first mindset that shaped the product from the beginning.

What are Ameba’s long-term ambitions?

We want to build the world’s first self-updating source of truth for physical goods in a company’s supply chain. That means moving from reactive firefighting to proactive operations, where teams can focus on innovation, product development, and sustainability instead of chasing delays.

Today, Ameba might look like a cutting-edge AI tool. Long-term, we want it to become the standard layer for commercial and supply chain execution, like ERP and PLM, but finally built for the speed and complexity of modern manufacturing.

Is Portugal a strategic market for Ameba? If so, why?

Yes, Portugal is a key market for Ameba. Many manufacturers have modernised the production floor, but commercial operations are still highly manual: pricing, customer communication, order tracking, and follow-ups take too much time and create risk.

Portugal has stayed globally relevant because the industry keeps reinventing itself and stays open to innovation. I often call Portugal the Silicon Valley of textile manufacturing for that reason. We’re also seeing a generational shift, with second-generation leaders eager to modernise and build on what their parents created. Ameba fits naturally into that transition – bringing speed, automation, and real-time visibility to the commercial side of the factory.

“Today, Ameba is a scalable platform with robust integrations.”

 

What role do you see Artificial Intelligence playing in the industry over the next few years?

AI isn’t a silver bullet, especially in supply chains, where you’re dealing with physical goods and real-world constraints. AI is only as good as the data behind it, and companies trying to “predict the future” on messy foundations will get burned.

The real opportunity right now is practical and massive: use AI to reduce manual work, capture data automatically, and build reliable operational visibility. Once that foundation exists, AI can help teams make better decisions; prevent delays, recommend actions, and run supply chains with far more control at SKU level.

In ten years, we won’t even call these tools “AI platforms.” This will simply be how modern operations run.

What does it mean in practice for Ameba to be SOC 2 and GDPR compliant? What guarantees do you provide regarding data security?

We treat data security like a core product feature, not an afterthought. Ameba only processes the specific threads, documents, and systems each customer authorises, inside a ring-fenced environment.

In practice, we guarantee strict customer-by-customer data isolation, encryption in transit and at rest, least-privilege access controls, detailed audit logs, continuous monitoring, and formal incident response processes. We never mix data across customers, and we don’t “train on” one customer’s information to benefit another.

Who is Ameba’s main target audience today: large groups, SMEs or both?

Both, as long as there’s real operational complexity. Ameba delivers the most value for manufacturers managing multiple suppliers, many SKUs, and high volumes of daily coordination.

Very small organisations or fully vertically integrated players may not feel the full impact, but for most textile and garment manufacturers in the middle, the efficiency gains are significant.

How do you support companies throughout implementation and usage? How long until results?

We work closely with customers from day one – mapping processes, configuring Ameba to their workflows, and integrating with existing systems. We’ve already built integrations with common tools in Portugal, including Protextil, which speeds up deployment.

We provide onboarding, training, and ongoing support, and most customers start seeing measurable results within a few weeks – because manual work drops quickly and visibility improves immediately.

What new opportunities open up once data is organised and available in real time?

Real-time data gives teams speed and confidence. Instead of relying on spreadsheets or chasing updates, they can prioritise faster, respond earlier, and make decisions based on the live status of every order.

That unlocks better planning, earlier risk detection, faster customer response, and continuous improvement – so teams can focus on growth instead of daily firefighting.

What competitive advantages do you see in the Portuguese textile and apparel industry?

Portugal combines deep manufacturing heritage with a real innovation mindset. Companies are known for quality, skilled teams, and reliability – while also investing heavily in modern machinery, advanced materials, and sustainability.

Portugal is also extremely agile: manufacturers can respond quickly to trends and deliver short lead times, supported by proximity to major European markets. That combination makes Portugal one of the strongest textile hubs globally.

What are the main supply chain management challenges Ameba addresses?

The biggest challenge is visibility. Information is scattered across ERPs, spreadsheets, emails, and internal teams, which makes it hard to respond quickly and accurately to changes in orders, availability, or customer requests.

On top of that, commercial and buying teams carry too much administrative workload—chasing updates, copying data, and managing exceptions manually. Ameba centralises and structures that information, automates follow-ups, and gives real-time insights so teams can move faster and operate with control.

Can digitalisation become a true driver of sustainability in textiles?

Yes—and the biggest impact will come from reducing waste, not just reporting it. Today, around 30% of clothing produced never reaches consumers, largely due to overproduction and rigid planning cycles.

AI can make supply chains more responsive, so brands and manufacturers can adjust orders mid-season, reduce excess inventory, and cut unnecessary production. That’s good for margins and a major win for sustainability.

What does the team behind Ameba look like?

Ameba is a technically complex product, and our team reflects that. We’re 16 people today, with 12 focused on engineering and product across backend, frontend, design, and product management.

Our team includes people from companies like Palantir, Microsoft, and Meta, plus a former quant engineer from a hedge fund. I’m extremely proud of the team we’ve built – because building a system like Ameba requires deep technical talent, high standards, and a lot of grit. Without this group, we simply couldn’t be building something this ambitious.