What is Tensor9?

There is a strong and growing need for privacy and security in enterprise software. To meet these requirements, SaaS and AI vendors often need to deliver software into cloud-prem and on-prem environments. Delivering an existing SaaS product into different environments is fundamentally challenging due to unique configurations, limited access, and security constraints. This often leads vendors to build and manage separate products, adding significant expense and distraction from delivering their core value proposition.

Tensor9 solves for any-prem deployments: Enabling SaaS and AI vendors to deliver their existing SaaS products directly into customer-owned environments, including cloud-prem and on-prem. This unlocks new markets for SaaS vendors without burdening the vendor with complex bespoke engineering and operations.

What challenges does Tensor9 solve?

Tensor9 solves the following key challenges:

• Deployment of software across customers: Tensor9 translates the vendor’s existing SaaS stack as defined via infrastructure as code for deployment into customer-owned environments, and continuously syncs updates to ensure consistency across customers.
• Portability: Tensor9 enables vendors to continue to use managed services and deploy cross-cloud, 3rd party, and OSS service equivalents per customer environment; where equivalents don’t exist, vendors can use Tensor9 to build for a subset of multi-cloud APIs and ensure portability from the get-go.
• Observability & operations: Tensor9 mirrors the deployment and operational state of a customer’s stack, allowing vendors to observe customer environments by synchronizing logs, metrics, and hardware failures—enabling vendors to observe, debug, and support customers as if they were using SaaS.
• Customer control: Tensor9 enables end customers to control how interactions are managed from their vendor, including maintenance windows, audit logs, and vendor access to private resources.

What makes our approach unique?

• Vendors keep their existing stack and tooling: Tensor9 enables vendors to leverage their existing stack without extensive rewrites; vendors don’t need to rearchitect their stack for Kubernetes or rewrite their Terraform, and Tensor9 provides practical paths to managed service equivalents or alternatives.
• Practical and thoughtful approach to simplification: Tensor9 enables vendors to surface versus hide customer constraints, so vendors can make informed trade-offs when there are incompatibilities between their stack and a customer’s environment.
• Operations and support are tactile: Tensor9 makes operating cloud-prem/on-prem as easy as SaaS wherever possible by mirroring the operational state of a customer’s environment so vendors are never in the dark when issues occur.
• Self-serve and easy to get started: Tensor9 enables fast-moving SaaS and AI companies to try out our solution on their own time, and provides a simple path to onboard new customers who don’t have infrastructure expertise.

What scenarios is Tensor9 great for?

• From SaaS to cloud-prem: A vendor has built their multi-tenant SaaS solution for AWS, and has leveraged infrastructure as code to ensure consistency in deployments. Prospective customers want to run the product on their own AWS accounts, and the vendor wants to serve these customers as quickly as possible.
• From Kubernetes-only to using cloud services: A vendor has built on Kubernetes to enable multi-cloud portability, but as they grew, started to use AWS services to fill in the gaps for capabilities such as databases and queues. Now a prospective customer wants to run it on their own GCP or Azure account (which happens to be their cloud of choice), due to security controls.
• Multi-cloud portability: A vendor has built their multi-tenant or single-tenant SaaS solution for AWS, and has leveraged infrastructure as code to ensure consistency in deployments. Prospective customers want to run the product on their own GCP or Azure account, and the vendor wants to serve these customers as quickly as possible.