How Didero is Solving the Physical Supply Chain Crisis
While much of the technology sector spent years debating whether artificial intelligence could automate creative work, a New York-based startup has focused on a different challenge: reducing the operational burden of running global supply chains.
Inspired by Denis Diderot's revolutionary 1751 EncyclopĂŠdie project, which sought to organise the fragmented practical knowledge of tradespeople and craftsmen, Didero is applying a similar principle to modern procurement. The company uses AI to transform the vast quantities of information scattered across emails, PDFs, spreadsheets and supplier communications into structured, actionable workflows.
In doing so, Didero is tackling one of the most persistent challenges in direct procurement: turning fragmented information into operational intelligence that can be acted upon automatically.
Direct procurement in the crosshairs
Unlike many procurement platforms that focus primarily on indirect spending and internal purchasing processes, Didero is designed specifically for direct procurementâthe raw materials, components and production inputs that keep manufacturing operations running.
Global trade remains heavily dependent on natural language communication, with suppliers and buyers exchanging information through emails, purchase orders, spreadsheets, messaging platforms and shipping documentation. While enterprise resource planning (ERP) systems provide systems of record, much of the operational work required to manage procurement still takes place outside those platforms.
Didero addresses this challenge through a coordinated network of AI agents that sit directly on top of existing ERP environments such as SAP, Oracle and Microsoft Dynamics, eliminating the need for organisations to undertake major infrastructure replacement projects.
The platform reads incoming communications across multiple channels, extracting contract variables, minimum order quantities, pricing information and delivery terms. Routine purchase orders can be issued, acknowledged and reconciled automatically.
The system only escalates activity to procurement teams through what Didero calls an "Exception Queue", surfacing issues when predefined tolerance thresholds are breached. These may include invoice price discrepancies, unexpected lead-time extensions or supply disruptions. Rather than simply flagging the issue, the platform presents pre-analysed alternatives and recommended next steps.
The platform is designed to enable procurement teams to spend less time managing transactions and more time focusing on supplier strategy, risk management and commercial decision-making.
Bridging the orchestration gap
The rise of AI across enterprise environments has introduced a new challenge: orchestration.
Many organisations are deploying multiple AI tools across different functions, yet those systems often operate independently from one another. In highly interconnected supply chains, disconnected automation can create new inefficiencies rather than eliminate existing ones.
Didero's approach centres on creating an orchestration layer that connects sourcing activity, supplier communications, accounts payable workflows and production planning into a single operational framework.
The platform is designed to understand supply chain-specific processes and terminology, enabling it to automate activities that traditionally required extensive human intervention. These include running Request for Quotation (RFQ) events, chasing supplier acknowledgements, processing invoices and continuously updating supplier performance data.
Among the company's customers is sustainable packaging manufacturer Footprint, which uses the platform to streamline supplier communications and accelerate procurement workflows across complex supply networks.
For manufacturers facing increasing supply chain volatility, the ability to automate routine procurement execution while maintaining human oversight is becoming an increasingly attractive proposition.
As Tim Spencer, CEO of Didero, says: "Global trade runs on natural language communication. The goal is to go from 'I need a good' to payment without having to lift a finger."
Capital infusion for growth
The funding round reflects investor confidence in AI-driven procurement automation and its potential operational impact, as Didero reports being deployed with more than 30 manufacturing and distribution customers.
Didero raised a US$30m Series A co-led by Chemistry and Headline, with participation from Microsoftâs venture fund M12.
Existing investors, including First Round Capital, Construct Capital, BoxGroup and AI Grant, also participated in the round, signalling continued confidence in the company's growth trajectory.
The new capital will support product development, engineering expansion and customer success initiatives, while helping Didero extend its autonomous capabilities into adjacent supply chain functions, including international payments and logistics orchestration.
Part of Didero's appeal lies in the experience of its founding team, whose backgrounds combine operational procurement expertise with deep technical capability.
Tim Spencer conceived the company after experiencing the challenges of managing thousands of suppliers during his time building e-commerce aggregator Markai throughout the pandemic. The experience exposed the limitations of manual procurement processes and highlighted the opportunity for automation.
He is joined by Lorenz Pallhuber, a former McKinsey procurement specialist with extensive experience analysing enterprise purchasing operations, and Tom Petit, former technical co-founder of Landis, who brings expertise in machine learning infrastructure and enterprise software development.
Together, the trio have built a platform rooted in practical supply chain challenges rather than purely theoretical AI applications.
From copilot to autopilot
The broader significance of Didero's approach extends beyond procurement software.
For decades, procurement technology has focused on visibility, reporting and workflow management. The latest generation of AI tools has improved access to information, but many still function primarily as assistants that support human decision-making.
Didero is pursuing a different model: autonomous execution.
By enabling software agents to carry out routine procurement activities independently and only involve humans when exceptions occur, the company is helping redefine how procurement work is performed.
Whether autonomous procurement ultimately becomes the dominant operating model remains to be seen. However, as manufacturers contend with increasing supply chain complexity, labour shortages, geopolitical uncertainty and growing pressure to improve efficiency, technologies capable of executing routine procurement work autonomously are moving rapidly from experimentation to practical application.
For procurement leaders seeking to do more with leaner teams, the future may not be better dashboards. It may be supply chains that increasingly run themselves.
