If you want people to adopt your AI product, the deployment story has to be as strong as the features.
Over the past few decades, the software industry has gone through multiple major transitions. Each one reshaped not only how products are delivered, but also how they are trusted.
- In the Client-Server Era (circa 2000), apps like SAP and PeopleSoft were purchased and deployed by the customer in their own "on-prem" environment. The customer was in control, but also took on the operational complexity of everything from procuring and deploying hardware to the system software and the apps themselves.
- In the SaaS Era (circa 2010s), apps such as Salesforce and Workday ran in the provider's cloud and were delivered through the browser. While this simplified operations for the customer, it also meant that the customer data was trapped in these applications, with sometimes ambiguous data ownership and usage rules.
- Today, we are entering the Agentic Era. Agentic apps promise to deliver an unprecedented productivity boost, but to do so, they need access to the most sensitive business data: conversations, documents, decisions. Customers do not want to transfer such data to an unknown and untrusted external provider's environment. Instead, they expect these products to run inside their cloud accounts (whether it be AWS, GCP, or any other), with their compliance, and under their security controls.
This is not a small adjustment. It is the foundation of how the next generation of software will be trusted and adopted.
Why the Agentic Era Changes the Rules
AI products are not like SaaS tools. They do not just manage workflows, they ingest and act on the crown jewels of a business. To succeed in this environment, three conditions must hold true:
- Data stays with the customer: no leaking sensitive content outside their environment.
- Deployments work across clouds: AWS, GCP, Azure, or wherever the customer operates.
- Security and compliance are built in: IAM, networking, and policies set up correctly from day one.
This is not a technical detail. It is the trust layer that determines whether adoption happens at all.
ekai's Example
ekai is an AI digital twin that boosts productivity by capturing meetings, surfacing action items, and acting as a Slack companion. To be trusted, it has to run inside the customer's cloud account.
ekai needed a single deployment solution that could run on any cloud and deliver a consistent, reliable experience with the same features everywhere. Like many AI builders, they faced the challenge of providing secure, compliant deployments across AWS, GCP, and other environments without spending weeks on custom DevOps for each customer.
That is where Defang came in.
With Defang, ekai defines its application once in Docker Compose. Defang turns that definition into a production-ready deployment inside the customer's own cloud account. Compute, storage, networking, IAM roles, security groups, and even managed LLMs are provisioned automatically, following best practices for each cloud.
What used to take weeks of engineering now happens in hours. More importantly, every deployment is secure, compliant, and customer-owned.
"Defang was the ideal choice for us. We simply describe ekai as a Docker Compose application, and Defang takes care of everything else. From compute and storage to IAM roles and managed LLMs, Defang ensures our deployments are secure, scalable, and cloud-native. That is a huge benefit for us and for our customers."
Ash Tiwari, Founder & CEO, ekai
Defang and the Agentic Era
ekai is not an isolated case. It is a preview of what the Agentic Era demands. As AI products move deeper into mission-critical workflows, deployment will decide adoption.
Defang exists to make this possible.
- Define your app once, no matter the framework: CrewAI, LangGraph, AutoGen, Strands
- Deploy to any cloud in a single step
- Keep customer data inside customer environments
- Align deployments with cloud-native best practices automatically
Just as SaaS platforms unlocked a decade of cloud adoption, Defang is the foundation for customer-owned AI.
The Takeaway
In the Agentic Era, trust is the product. The next wave of AI adoption will be decided not by features, but by where and how products run. Companies that respect data ownership and deliver secure, cloud-native deployments will earn trust and scale. Those that do not will be left behind.
Defang is the invisible infrastructure making this era possible.
