Deployment
Deploy where the data lives. Verify where the work happens.
Sentiant runs inside your chosen boundary: private cloud, VPC, on-prem, edge, or a controlled hybrid setup. AI outputs are checked against trusted systems, workflow rules, permissions, and evidence before the process moves forward. The point is not just private deployment. It is verified execution inside the right boundary.
Boundary Status
CONTROLLED
Private cloud, VPC, on-prem, or edge
Runtime, contracts, connectors, and audit spine
Outputs checked before action
Exceptions route to human reviewers
Every check and approval logged
01 — Deployment Patterns
Four deployment patterns. One execution model.
Whether Sentiant runs in your cloud, on-prem, at the edge, or across a hybrid boundary, the same workflow contract, verification checks, and audit trail apply.
On-Premises
For high-control environments where models, data, workflow execution, and audit logs must stay inside the physical boundary. Supports air-gapped operation with no outbound connectivity required.
Air-gappedPhysical boundaryZero egress
Private VPC
For teams that want private AI execution inside their own cloud boundary. You control the keys, network policy, access paths, and data movement.
Customer-managed keysVPC isolationPrivate networking
Edge
For low-latency execution at a site, facility, branch, lab, or operational location. Works with intermittent connectivity and no cloud dependency at runtime.
Local executionOffline-capableSite-level deployment
Hybrid
For mixed environments where tasks are routed by data sensitivity, latency, risk, or policy. Sensitive workflows stay local. Lower-risk workloads can use approved cloud resources.
Policy-routedData-classifiedMulti-environment
02 — Same Controls, Everywhere
Verified execution
Private deployment is not the point. Verified execution inside the right boundary is.
Wherever Sentiant runs, the execution model stays the same.
Workflow contracts define the steps, roles, controls, and evidence required
Model outputs are constrained and inspected before use
Source-system checks verify facts against trusted records
Exceptions escalate to the right human reviewer
Every input, output, check, approval, and model version is logged
03 — Deployment Fit
Choose the boundary by risk, latency, and control.
Not every workflow needs the same deployment model. Sentiant can run close to the data, close to the operator, or across controlled environments depending on what the workflow is allowed to touch.
High-control workflows
On-Premises
Use when data cannot leave the physical boundary, outbound connectivity is restricted, and audit controls are strict. Avoid when the workflow depends heavily on cloud-only systems.
Enterprise cloud teams
Private VPC
Use when you need private AI execution inside existing cloud governance, identity, network, and key-management controls. Avoid when site latency or local autonomy is the primary constraint.
Site-level operations
Edge
Use when the work happens at a facility, plant, lab, branch, or field location with latency or connectivity constraints. Avoid when centralised cloud orchestration is mandatory.
Mixed-sensitivity workflows
Hybrid
Use when sensitive steps stay local while approved low-risk tasks use controlled cloud resources. Avoid when policy routing is unclear or data classification is immature.
04 — What Gets Deployed
Installed surface
Runtime components that let AI execute, verify, escalate, and record work inside your boundary.
Sentiant is not a hosted agent pointed at your systems. Each deployment includes the runtime components needed to execute, verify, escalate, and record AI-assisted workflow steps inside the chosen boundary.
Local runtime
Executes workflow steps, model calls, checks, and state transitions inside the deployment boundary.
Workflow contracts
Define steps, roles, required evidence, source checks, escalation paths, and allowed transitions.
Verification connectors
Connect to approved systems of record such as ERP, QMS, EAM, document stores, identity systems, and internal APIs.
Private inference layer
Runs selected models locally, at the edge, or inside a controlled cloud environment.
Audit event spine
Records inputs, outputs, checks, approvals, exceptions, model versions, and workflow state changes.
Operations console
Gives authorised teams visibility into workflow status, failures, escalations, and audit evidence.
05 — Regulated Sectors
Applied where privacy, evidence, and operational control are part of the job.
Pharmaceutical manufacturing
GxP-aligned deviation triage, CAPA support, batch record review, and quality evidence management for audit-ready environments.
Energy and utilities
Incident response, shift handover, permit-to-work workflows, and operational reporting for site-level environments where connectivity and latency matter.
Financial services
Regulatory evidence packs, compliance workflow automation, control testing, and document processing with private deployment and source-level traceability.
Healthcare operations
Operational handover, quality workflows, regulated documentation, and privacy-sensitive process support for healthcare environments.
Industrial manufacturing
Quality control workflows, maintenance procedures, supplier document review, and operator assistance with local execution and full traceability.
Public sector and critical infrastructure
Evidence-heavy operational workflows, controlled document processing, incident reporting, and data-sovereign AI execution for environments where privacy, assurance, and accountability are mandatory.
Deployment Fit
See how verified execution fits your environment.
Tell us about your workflow, systems, risk profile, and deployment boundary. We’ll show you the right deployment pattern, verification checks, and audit controls for moving from pilot to production.