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One moment.
NODES deploys single-tenant inside your cloud account. Model training, inference, scoring, and every decision trace run on infrastructure you own. No external API calls. No OpenAI or Anthropic in your supply chain. No data leaves the boundary, because there is nowhere for it to go. The same boundary applies to every decision the brain makes, regardless of decision type.
Most AI vendor reviews collapse at data residency, model supply chain, or egress controls. NODES answers those three objections structurally: there is nothing to approve because there is nothing that leaves your cloud account.
The side-by-side below is a redacted composite of one actual deployment timeline versus the prior vendor stack that procurement, security, and legal had already rejected.
Four lanes, one account, one tenant: control plane, model plane, customer data, audit. No shared infrastructure with another customer. No NODES-operated inference. No path to the public internet from anything that touches your data.
NODES ships a fine-tuned open-source foundation model and calibrates it inside your boundary on your four-year production trace. There is no call out to a hosted LLM provider at training time, at inference time, or in the audit stream.
Every weight under every inference is the weight the customer owns. Retrains happen in-cluster, on rolling 18-month production. Weight artifacts never leave the VPC.
The ledger your counsel will screenshot. Each row is enforced by network policy, IAM, or KMS (not just documented). Retention is customer-configurable; defaults shown.
Controls are implemented in the deployment, not bolted on in policy. Every certification below is backed by the same single-tenant-VPC architecture. The architecture is the control.
# One module. Your account. Your KMS. Your subnets. module "nodes" { source = "nodes-inc/nodes/aws" version = "2026.4" # deployment boundary vpc_id = var.vpc_id private_subnets = var.private_subnets allow_egress = false # enforced · default-deny # customer-held keys kms_key_arn = aws_kms_key.nodes.arn weights_bucket = aws_s3_bucket.weights.id object_lock = "compliance" # identity + audit sso_provider = "okta" siem_sink = var.splunk_hec_endpoint audit_stream = true # model model_artifact = "nodes-substrate-2026.04" retrain_cadence = "quarterly" inference_gpu = "g5.2xlarge" }
Answered once, here, with the spec IDs your counsel will want to cite. For anything not covered, the architecture review (Day 01) is a working session with a NODES security engineer, not a sales call.
No. The deployment enforces a default-deny egress policy at the subnet level. Candidate, employee, ticket, deal, and decision data is read through from your source systems (ATS, HRIS, CRM, ticketing, calendar, performance database) and never copied out of your cloud account. Inference request bodies, scored responses, and decision traces all stay in-cluster. The only opt-in traffic that ever leaves is aggregate operational telemetry with every PII field scrubbed server-side before it is emitted, and that opt-in can be turned off in Terraform.
You do. The weights artifact is delivered into a bucket you own, encrypted with a KMS key you hold. The NODES service role has read access, scoped to the cluster; the artifact cannot be exported. Revoke the KMS key and inference stops, which is what every customer tests on Day 07 of deployment.
No. NODES fine-tunes an open-source foundation model with a pinned digest; there is no call out to a hosted LLM provider at training, fine-tune, or inference time. The DPA lists zero external subprocessors for model operations. This is the question that stalls most vendor reviews; here, it is answered by the deployment topology, not by policy.
In-cluster, on your data, on a quarterly cadence, producing a new signed weights artifact that lives only in your VPC. Retrain jobs run under the NODES service role with scoped IAM. NODES does not pull your data back to retrain a shared model. There is no shared model. Your weights are yours.
The deployment keeps running. The weights are in your bucket under your KMS key. The inference binary is in your cluster. The Terraform module and Helm chart are pinned in your CI. A source-escrow clause in the master agreement gives you the right to rebuild the binary from source after a triggering event. "Lights-on without NODES" is a stated design goal.
To your HRIS or ATS, never to NODES. Because candidate and employee records live in your source-of-truth systems and are read through into NODES only at scoring time, a delete or export request fulfilled in your HRIS is automatically reflected in NODES on the next read. Decision traces bound to deleted subjects are tombstoned on the same schedule.
Yes. The Terraform module runs in AWS GovCloud, Azure Government, and GCP Assured Workloads out of the box. For air-gapped environments NODES ships weights, binaries, and the Helm chart as signed offline artifacts. Retrains are triggered by a scheduled job inside the air-gapped cluster, with no return path. Talk to the architecture review team for the offline delivery process.
NODES walks through the deployment diagram against your cloud account topology, shares the SOC 2 report, and leaves you with a DPA template and a Terraform plan your team can review offline. Most reviewers come out with enough to open an internal architecture ticket the same day.