Data and AI sovereignty
your own environment.
NeuralSeek runs in your cloud, your region or on your own hardware. Disconnect it from the internet and it keeps working.
Deployment
It runs where your data already lives.
Run it where your data already is. The same software runs in a cloud account or a locked room, with every feature.
Can we see it working before we commit?SaaS
Start with our SaaS, run by NeuralSeek on GCP, Azure, AWS or IBM Cloud. It is the same software you would run yourself, so when residency becomes the requirement, you move it into your own environment without rebuilding.
Can it run in our own cloud account, under our own keys?Private cloud
The same container in your own account, under your network policy and your key management, in any isolated environment you run. Retrieval, logging and the audit trail run in your region with it, and you decide which model it calls: one you host for the sensitive work, a cloud model for the rest, switched task by task.
Our government requires our data to stay inside our borders.Sovereign cloud
Deploy it from your own registry into a region or operator your regulator already recognizes. Everything stays local, production and non-production, high availability and disaster recovery included, so your data stays inside your borders.
Will it fit the platform we already run?OpenShift
NeuralSeek is containerized end to end and runs on Red Hat OpenShift, alongside the rest of your regulated workloads. Your admission, network and secret-management rules apply to it exactly as they do to everything else on the cluster.
What happens if we unplug it from the internet?Air-gapped on-prem
It keeps working. Behind your firewall, or as a single appliance on IBM Fusion with hardware and software delivered together, it runs offline: open models on your own GPUs, your own vector database, everything in the building. With the model running locally, you pay no per-token charges for it.
Wherever it runs
The same controls wherever it runs
Encryption, tenant isolation and PII masking come with every deployment, from SaaS to air-gapped.
Encrypted in transit and at rest
Data residency
Your data stays where you put it
NeuralSeek runs in your tenant, in the region you choose, or on hardware in your own building, and retrieval, orchestration, logging and the audit trail run there with it. Logs go to a store you own. Point it at a model you host and every call stays inside too.
Full audit trail
AI sovereignty
Choose your model, and change it
You choose the model, and you can change it whenever you want.
Model-agnostic by design
Swap the underlying model whenever you want, with no rebuild. Your data, your guardrails and your applications stay as they are. Route by task, too: sensitive work to a model you host, the rest to a hosted one.
Your own provider keys
Bring your own keys to a model provider, so the commercial relationship and the entitlement that comes with it are yours.
Open models on your own GPUs
Run open-source models on hardware you own, next to everything else, so every model call stays on your network.
Questions buyers ask
Short answers on models, data and control.
What if the model we depend on is withdrawn or restricted?
Then you change a setting. The model is one layer inside the container, so your data, your guardrails and your applications stay as they are when it changes. Run open models on your own GPUs and everything you depend on stays in your environment.
What if a court or agency demands our data from a provider?
A hosted model provider keeps its own record of your queries, under a retention policy you did not write. Run the model in your own environment and the only copy is the one in your log store, kept for as long as your policy says, with no third party holding a copy.
Will the answers change when a provider changes its model?
Not unless you decide they should. A hosted model can change underneath you: updated, retuned or slower under load. A model on your own hardware stays the version you tested. When a new one comes out, you test it on your schedule and switch when it passes.
We already use AI in several products. Why is this different?
Each AI tool is its own data path, its own agreement and its own review. One platform in your environment gives you one review, one audit trail and one place to look.
If we lock AI down, won't people just use their own?
They will, and many already do. Blocking tools doesn't stop it, but giving people an approved one does. Because NeuralSeek runs in your environment with guardrails, logging and governance on every answer, it can be the tool you hand everyone on day one.
Where do our meeting notes end up?
A meeting assistant that runs as someone else's service sends the conversation to wherever that service runs. NeuralWorks, the assistant built on NeuralSeek, prepares for your meetings and follows up on them in your own environment, with the models you provide, so the conversation stays on your servers.
Do you train on our data?
No. Neither NeuralSeek nor its subprocessors use your prompts, documents or interaction logs to train models. Keys are separated per tenant, and every deployment works this way.
Audited, and under your controls
Run NeuralSeek in an environment you already audit and it works under your network controls, key management, logging and incident process. NeuralSeek itself holds SOC 1 and SOC 2 Type II reports and is HIPAA compliant.
Audited
SOC 2 Type II
Audited every year.
Held by NeuralSeek.
See certifications for details.
Start building with NeuralSeek today.
Sign up online and start with a two-week trial, or talk to a NeuralSeek expert about running it in your own cloud.