Standardize

Deployments Across Customer Environments

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GKE
GBQ

Multiple product variants for each environment

Little to no insight into customer environments

Months of custom work or revenue turned away

Multiple versions to patch and support

Constraints to minimize complexity

Tensor9 is an enterprise any-prem platform. We enable software vendors to deliver their product inside customer infrastructure — whether you’re building that capability for the first time or replacing a costly, manual process that doesn’t scale. We compile your existing stack for any target environment so sensitive
data stays with the customer.

For most vendors, we analyze and compile your existing stack in 1-2 weeks, and your first customer environment can be live by week 3-4. There’s no re-architecture required and no dedicated platform team to hire or re-allocate. This is the single biggest misconception vendors have about working with Tensor9 — they expect a multi-month engagement, and they’re surprised when their first customer is live in weeks.

  • From SaaS to BYOC: You have an AWS SaaS built with IaC. Enterprise customers now demand to run the product in their own AWS accounts, requiring immediate delivery without heavy engineering.
  • From Kubernetes-only to using cloud services: You augmented your Kubernetes stack with AWS services (databases, queues). Now, customers require deployment on Azure or GCP for security reasons, but the app is tied to AWS dependencies.
  • Multi-Cloud Portability: Your SaaS is optimized for AWS. New prospects demand it run on Google Cloud or Azure, requiring instant portability to unlock the market without re-platforming.
  • Standardizing Existing Private Deployments: You already deliver on-prem or into customer VPCs, but every customer is a snowflake — different scripts, different processes, different support burden. Tensor9 replaces the patchwork with a single, standardized delivery and operations model across all your customers.

You can deploy to virtually any environment: customer-owned VPCs (AWS, Azure, GCP), private data centers, all with or without Kubernetes. The deployment experience remains consistent for you, regardless of the underlying infrastructure.

No. Tensor9 automatically translates your existing cloud-native stack into local equivalents for any environment, so you can deploy anywhere without maintaining separate codebases. 

Tensor9 aggregates metrics, logs, and traces from all your distributed deployments and forwards them to your existing tools like Datadog or Prometheus. You can see the health of your entire fleet in real-time, just as if it were running in your own cloud.

Your application runs entirely within your customer’s sovereign boundary, and their sensitive data never touches our control plane. Tensor9 only receives metadata from customer environments. This can include things like:

  • The versions of Tensor9 software running in your and your customers’ environments.
  • The number of Tensor9 controllers in each environment.
  • The memory/cpu/network capacity of each machine.

No, it complements it. Deploying to customer-managed Kubernetes clusters provides flexibility for customers who want to run appliances in their own Kubernetes infrastructure, whether on-premises, in private data centers, or on self-managed cloud Kubernetes.

Ready to Deliver Your Anywhere?

We charge an annual fee for the platform, as well as a fee per customer appliance (a deployment of your software in a customer environment). The platform fee is intentionally low: the time to value with Tensor9 is minimal as you bring your existing stack.

You can purchase the full Tensor9 platform, or purchase the Deploy or Observe & Operate products individually.

No. You manage your relationship with your own customer. Tensor9 white-labels our product, and will act as part of your team if you ever would like us to interact with your customer.

Each of your end customers will typically need a single appliance. If an end customer needs multiple isolated instances of your application, or has multiple geographically separated regions, then that customer will need multiple appliances.

The end customer does; the appliance runs in their cloud account.