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SG procurement firm Eezee raises $5m pre-series B

Eezee, a procurement platform based in Southeast Asia, has raised US$5 million in a pre-series B funding round led by Korea Investment Partners Southeast Asia, with existing investors including Kickstart Ventures and Wavemaker Ventures participating.

The funding will support Eezee’s expansion across Southeast Asia, now including Thailand, and further development of its AI-powered procurement tools, RFQBot and ProcureFlow.

The company’s platform aims to automate enterprise procurement, especially for low-value, long-tail purchases, claiming to reduce procurement time from days to minutes and cut costs by at least 20%.

Eezee reported operational profitability in Indonesia and Malaysia, with plans to roll out AI tools across multiple markets in 2026.

The company intends to reach group-level profitability in the second half of 2026 while expanding its regional presence and AI offerings.

🔗 Source: Eezee

🧠 Food for thought

Implications, context, and why it matters.

Eezee’s AI push builds on an established enterprise business

  • AI now gets the attention, yet Eezee is not new. It started in 2016 and spent years building a B2B marketplace across Southeast Asia 1.
  • Eezee earned enterprise trust early when Shell became its first large customer. That work involved complex procurement long before the AI rollout 1.
  • ProcureFlow launched in 2024. It aims to handle demand spikes without adding staff 2.
  • The tagline, “Scale Procurement, Not Headcount,” puts the focus on smoother operations rather than only cutting costs 1.

The funding hints at a new playbook for enterprise AI adoption

  • The approach suggests procurement teams may spend less time on small, long-tail buys while keeping a grip on budgets.
  • Automation can move staff time toward higher-value contracts and supplier relationships 1.
  • Positioning AI as support for employees helps win internal approval.
  • Eezee lowers adoption risk with a pilot that charges only after results are proven. This model could spread among enterprise AI vendors that need to earn trust fast 3.

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