Solution
Use AI on real work without sending the work outside.
Nexus runs self-hosted models next to the systems and documents they reason about, so prompts, retrieved context, outputs and decisions stay inside your infrastructure.
Deterministic first, model second, person last
- model endpoints
- Self-hostedmodel endpoints
- knowledge bases
- Privateknowledge bases
- before and after inference
- Guardrailsbefore and after inference
- capable
- Air-gappedcapable
The problem
The useful cases are the ones you cannot send away.
The documents worth classifying are contracts, claims, invoices and case files. For regulated and public-sector organizations, routing those through an external model API is the reason AI programmes stall.
Automate the known. Apply AI to the ambiguous. Keep people in control.
The approach
Models are a step in a governed workflow, not a product bolted beside one.
Model registry
Registered endpoints with the workflows permitted to call them, so model use is inventoried rather than improvised.
Private knowledge
Retrieval runs against your own indexed content, with source references carried into the output.
Guardrails
Input and output checks run around inference, and failures route to a branch rather than continuing silently.
Human review
Model output is a proposal until a named reviewer confirms or corrects it.
How it works
What actually happens on each run.
Rules eliminate the clear cases
Policy checks and validation run first in code nodes. Cases that pass or fail definitively never reach a model, which keeps inference cost and review load on the cases that need judgment.
Retrieval assembles the context
The workflow gathers records from your systems and passages from your knowledge base before the prompt is built, so the model reasons over current data rather than training-time memory.
Inference stays inside the boundary
The model endpoint runs on your infrastructure. In an air-gapped deployment the same workflow runs unchanged, because nothing in the path requires external connectivity.
Decisions become institutional intelligence
Reviewer corrections are captured as structured data and used by your teams to improve prompts, retrieval sources, evaluation sets and policies. Nexus does not retrain anything automatically.
Worked example
Inbound claim triage.
A claim arrives by email. Rules validate the policy number and coverage window. A self-hosted model summarizes the correspondence and extracts the loss description. Anything above threshold pauses for an adjuster, whose decision and reason are recorded with the run, then written back to the claims system.
Where it runs
On your hardware, in your cloud, or with no connectivity at all.
Nexus is Kubernetes-agnostic and deploys on-premises, in private or sovereign cloud, or fully air-gapped. Not an on-premises connector to a cloud platform. A platform that runs inside your environment.
Architecture session
Bring the AI case your current tooling cannot take.
Tell us the documents, the systems they belong to and the decision at the end. We will show how the run looks inside your boundary.