SinansysEnterprise readiness
What your security and procurement teams will ask.
You should not have to get three meetings into a conversation before finding out whether we can meet your deployment, data and security requirements. The answers are below, in writing, before you call.
Who are we contracting with?
A New York limited liability company established in 2025, and a subsidiary of RecycleGO, founded in 2016.
Where can Sinansys run?
Microsoft Azure, AWS, customer-controlled cloud, or private and on-premises infrastructure.
Where does our data live?
U.S. and EU-resident deployments are available. Private deployments keep data inside customer-controlled infrastructure.
Does our data have to leave our environment for AI processing?
Private deployments keep customer data, models, AI inference and compute inside your environment, including locally hosted open-source models.
Can Sinansys work with our security controls?
Private deployments integrate with your identity, network, logging, monitoring and security infrastructure.
Who owns the platform?
Core technology and methodology are protected by granted and pending U.S. patents. Third-party technologies and data are used under applicable licenses.
Who else processes our data?
We provide the applicable subprocessor list during security review. Private deployment materially reduces external services.
Do you carry enterprise insurance?
Technology errors and omissions at $1M/$2M, cyber liability at $1M/$2M, and commercial general liability at $1M/$2M. Certificate available on request.
Security review
What we send, and when.
Tell us which deployment you are evaluating and we scope the package to it. A private deployment removes most of the third-party surface, so the review is materially shorter than for a managed one.
Architecture and data flow
Component diagram, trust boundaries, where customer data comes to rest, and which processing happens inside your environment under the deployment you are considering.
Subprocessor list
Scoped to your deployment model, with the purpose and data category for each. Private deployment materially reduces this list.
Certificate of insurance
Technology errors and omissions, cyber liability, and commercial general liability, each at $1M per occurrence and $2M aggregate.
Model and inference handling
Which models run where, what is retained, and how to configure a deployment where nothing leaves your network for AI processing.
Deployment options
Azure, AWS, your own cloud account, or on-premises. The full comparison is on the platform page.
Start here
Tell us which deployment you are evaluating.
We will send the architecture, security and data-handling package that applies to it, along with the subprocessor list for that model.