Gartner, the research firm, predicts more than 40% of "agentic" AI projects, meaning AI systems built to take actions rather than just answer questions, will be scrapped by the end of 2027.
The reported reason isn't that the underlying models are getting things wrong.
It's what Natzka, the startup pitching a fix, calls an "orchestration wall": company data is scattered across disconnected systems, and AI tools sit outside the actual workflows where decisions get made.
The result is an AI that can tell you what to do, but has no way to actually do it.
What Natzka is selling instead
Natzka's product is a layer that sits between the AI and the company's existing systems, acting as a kind of translator and rulebook combined.
It bundles together the context an AI needs, the business rules it must follow, who is allowed to approve what, and a memory of past decisions, essentially giving the AI the institutional knowledge a new employee would normally spend months learning.
Paired with that "brain," the system has "hands": the ability to actually carry out actions across different company functions, with humans still able to step in and approve or override.
Why the guardrails matter as much as the AI
The pitch layers approval steps, defined roles, and audit trails on top of the automated workflows, so a human can always see who decided what and why.
That lets a company measure success in concrete terms: how long a decision takes, how long it takes to act on it, and whether the risk controls actually held up.
The bigger trend
Natzka's argument mirrors a wider shift among AI vendors and analysts in 2026: many now say AI adoption is failing for organisational reasons, poor workflow design and weak governance, rather than because the models themselves aren't capable enough.
The company is betting that the way to fix stalled AI pilots isn't a better model, but a better bridge between the model and the messy reality of how a company actually runs.
