Conmeet raises €1.3M to modernise ConTech

Conmeet’s €1.3M pre-seed: what’s confirmed

Conmeet has closed a €1.3 million pre-seed financing round to accelerate go-to-market for its platform serving construction and trade businesses. The round is led by May Ventures, and the founders also participated with meaningful personal capital—an uncommon structure at pre-seed that markets often read as high internal conviction. The company is based in Borken (North Rhine-Westphalia) and positions its product as an AI-enabled cloud platform built for process-heavy, operationally complex firms rather than “single-workflow” point tools.

The founding team includes CEO Benedikt Kisner, CTO Leandro Ananias, and COO Lennart Eckerlein, and they developed the product for roughly two years in stealth before reaching early customer usage. Reporting also notes Kisner’s prior entrepreneurial track record, including building the netgo group and later exiting via a sale to a private equity buyer, with the business described as having scaled to over 1,300 employees and nine-figure revenues at the time. Conmeet says early customers are already live, and it is targeting a “sweet spot” of process-oriented construction and trade companies sized roughly 10 to 500 employees.

For our readers at the ai world organisation, the headline isn’t just the cheque size; it’s the product thesis: construction and trades are finally seeing platforms that try to unify operational data, workflow, collaboration, and finance—then use AI to compress admin overhead while preserving the controls these businesses need. This kind of “operations OS” direction is likely to surface repeatedly at the ai world summit and in ai conferences by ai world, especially as AI agents become less of a demo and more of a deployment discussion.

Why construction ops is a perfect “AI + workflow” battleground

Construction and trades businesses run on coordination: quotes, schedules, crews, subcontractors, documentation, compliance, billing, and change management all move in parallel, often under tight cashflow constraints and with constant on-site variability. When software stacks are stitched together tool-by-tool, teams can end up duplicating entries, reconciling mismatched project states, and chasing approvals across channels—which creates delay, error, and “invisible” cost that scales with every additional job and partner.

This is exactly why ConTech has become one of the most pragmatic places for applied AI: the work is messy, repetitive, and document-heavy, but the value of better orchestration is immediate. In practice, AI’s most bankable promise here isn’t flashy generative output; it’s reducing admin time, preventing rework, improving project visibility, and lowering coordination friction across company boundaries. If you’re building a product for this market, you win by making the business run cleaner—not by sounding futuristic.

From the ai world organisation lens, there’s also a broader macro driver: talent scarcity and productivity pressure are pushing traditional industries to adopt automation faster than they otherwise would. That same pressure is what brings many industrial leaders to ai world organisation events and to the ai world summit, because they’re not shopping for “AI inspiration”—they’re shopping for operating advantage.

What conmeet is building (and why “all-in-one” matters)

Conmeet is positioning itself as a cloud-native platform that consolidates multiple business functions—such as CRM, ERP, project management, controlling, banking, and communication—on a shared database, with AI-supported workflows intended to automate recurring tasks and manage complex processes. The company’s framing is that mid-sized construction and trade firms often juggle many separate tools and still don’t get a coherent, end-to-end view of projects, costs, and operational execution. One report explicitly describes this fragmentation as companies using roughly 5 to 8 different software solutions across core functions, which can create data silos, extra administrative effort, and limited transparency.

In that context, “all-in-one” is not a marketing slogan—it’s a bet on outcomes. A unified system can reduce duplicate data entry, tighten audit trails, and make reporting meaningful because everyone is working off the same project truth. It can also make AI more useful, because models and automations improve when they can see end-to-end context rather than isolated slices of activity.

Conmeet also highlights an ecosystem-style approach designed to support structured collaboration across company boundaries, for example between subcontractors and project partners. The platform includes collaboration features such as shared project hierarchies, digital construction diaries, and integrated defect management—functions that can create compounding value as more partners operate inside the same shared workflows. This is strategically important because construction supply chains are networked by default; the software that “wins” often wins because it becomes the path of least resistance for multi-party coordination.

For ai world summit 2025 / 2026 conversations, this is a useful case study in how vertical AI products are evolving: the product moat increasingly comes from workflow depth, integrated data, and network participation—not from a generic model feature anyone can copy.

Where the money goes: scaling now, agents later

The announced plan for the new capital is practical: expand sales and marketing, strengthen engineering, and deepen AI capabilities. This is consistent with what a pre-seed “exit stealth” moment usually requires: move from product build to repeatable acquisition, onboarding, and retention loops, while still improving the core product fast enough to outpace incumbents and point-solution challengers.

The longer-term roadmap described in reporting is also notable: Conmeet wants to become a central AI platform across the real estate value chain and is explicitly focused on AI agents that can increasingly run entire business processes more autonomously. In the same roadmap, it describes expanding a cross-industry ecosystem that could integrate additional stakeholders like architects, general contractors, facility management, and maintenance providers. If executed well, that roadmap would move the product from “company tool” to “industry coordination layer,” which is exactly where platform defensibility grows.

One report also claims the platform’s AI-driven automation could reduce administrative effort by roughly 20–40%, while still providing enterprise-grade functionality—a statement that, if validated in real deployments, becomes a very strong ROI narrative for an industry under constant margin pressure. As always, the real test is whether customers see those savings not just in week-one demos, but after months of live operation when edge cases, exceptions, and on-site reality hit.

At the ai world organisation, we often frame agentic AI in one simple question: “Which decisions and tasks can safely move from people to software, and under what controls?” Conmeet’s roadmap suggests it wants to answer that question inside construction operations—where the stakes include cost overruns, compliance exposure, and schedule risk.

What this means for ConTech—and why it belongs at the AI World Summit

Conmeet’s raise is a reminder that vertical AI isn’t only being built for digital-native sectors; it’s being built where coordination is expensive and mistakes are costly. The construction and trades segment is large, operationally complex, and historically underserved by truly integrated software—so even incremental automation can unlock significant value. The more these platforms can unify data and reduce operational noise, the more feasible it becomes to layer AI agents on top without creating “automation chaos.”

From a market perspective, conmeet is also choosing a specific battlefield: not just digitising small shops, but targeting the “upper mid-market” where firms are big enough to pay for a full operating system and feel the pain of fragmentation every day. That segment is often where switching costs are high, integrations get messy, and adoption requires change management—which means vendors must bring implementation discipline, training, and trust alongside product.

This is exactly the kind of story we like to connect to theaiworld.org readers: funding is the headline, but execution is the story. The most important follow-up questions are operational: How fast can conmeet onboard customers? How does it handle jobsite variability? What governance controls exist for AI-driven workflows? How does it integrate partners while maintaining permissions, audit trails, and accountability? Those questions shape real outcomes far more than “AI features.”

As we head into ai world summit 2025 / 2026 programming and continue to build ai world organisation events globally, ConTech is a track that deserves more stage time—because it’s a real-world testbed for applied AI, agentic workflows, and cross-company collaboration. The AI World Organisation’s broader focus on community and global summits is designed for exactly this kind of cross-industry learning: builders, software leaders, investors, and policymakers comparing notes on what works at scale.