Deployment Models

How and Where Kaevor Operates Within Your Environment

Kaevor supports four deployment models. Which one is appropriate depends on your organization’s governance requirements, data residency obligations, and risk posture — not on Kaevor’s preference.

This document describes each model, what it exposes and what it does not, and how to evaluate which option fits your environment.

Executive Summary

Model	Data Location	Governance Complexity	Typical Use
SaaS Cloud	Kaevor-managed	Low	Startups, technology companies
Dedicated Tenant	Kaevor-managed, isolated	Moderate	Fintech, large enterprises
Customer Hosted	Customer infrastructure	High	Banking, government, defense
Hybrid Signals	Mixed — raw data stays local	Variable	Healthcare, regulated sectors

All four models preserve the same core trust principles: Signals Over Content, Trust Boundaries, Data Sovereignty, Explainable Orchestration, and Enterprise Governance.

The Trust Spectrum

Organizations operate under different governance requirements. Kaevor’s deployment models are designed to serve this full spectrum without requiring any organization to compromise its standards.

Low Governance Environments — startups, technology companies, small businesses — typically prioritize deployment speed and operational simplicity over regulatory complexity.

Moderate Governance Environments — consulting firms, large enterprises, professional services organizations — require defined data handling, compliance capability, and audit access.

High Governance Environments — banking, healthcare, government, defense — require strict data sovereignty, infrastructure control, and the ability to demonstrate regulatory compliance at every layer.

Model 1 — SaaS Cloud

Signal sources connect directly to Kaevor’s managed cloud environment. Compatible sources include platforms such as Slack, Microsoft Teams, Google Workspace, Microsoft 365, and optional wearable integrations.

Signals → Kaevor Cloud → Contextual Intelligence

What this means:

Fastest path to deployment
Minimal infrastructure requirements
Managed operations and continuous updates
Data processed and stored in Kaevor-managed infrastructure

Best suited to: Startups, technology companies, and growing organizations where governance complexity is low and deployment speed is a priority.

Model 2 — Dedicated Tenant

A logically isolated environment within Kaevor-managed infrastructure. Infrastructure is managed by Kaevor but operates within dedicated boundaries, with separate data storage and enhanced governance controls.

Customer → Dedicated Environment → Dedicated Storage

What this means:

Tenant isolation: your environment is separated from other customers
Dedicated data storage boundaries
Enterprise-grade governance controls
Infrastructure operations remain with Kaevor

Best suited to: Fintech, insurance, large enterprises, and organizations operating under regulatory frameworks that require data separation but do not mandate self-hosted infrastructure.

Model 3 — Customer Hosted

The Kaevor runtime deploys entirely inside your infrastructure. All infrastructure control, security configuration, and data governance remain with your organization. Contextual intelligence capabilities are fully available; data never leaves your environment.

Customer Infrastructure → Kaevor Runtime

What this means:

Complete data residency within your environment
Your security policies and access controls apply directly
No data transmitted to Kaevor infrastructure during operation
Governance responsibility sits entirely with your organization

Best suited to: Banking, government agencies, defense contractors, and any sector where data residency and infrastructure sovereignty are non-negotiable requirements.

Model 4 — Hybrid Signals

Sensitive systems remain inside your environment. Only derived contextual signals are shared with Kaevor. This architecture keeps raw operational data entirely within your boundaries, while exporting only calculated signals — summaries of patterns, not the underlying content.

Sensitive Systems → Signal Extraction Layer → Kaevor

Signals that may be exported:

Meeting density
Communication intensity
Recovery availability
Interruption frequency
Workload indicators

Information never exported:

Message content
Email bodies
Meeting transcripts
Documents
Confidential records of any kind

What this means:

Contextual intelligence operates from signals only — not from raw content
Strongest privacy posture of the four models
Reduces compliance complexity in regulated environments
Enables deployment in environments where content access would otherwise be prohibited

Best suited to: Healthcare, banking, public sector, and any organization where privacy constraints would otherwise block deployment.

Why Hybrid Signals Is Architecturally Distinctive

Most intelligent systems require raw data to operate. Kaevor frequently does not. The platform was designed around contextual understanding rather than content analysis, which creates deployment possibilities that would not otherwise be achievable in sensitive environments.

Organizations can benefit from contextual intelligence while maintaining strict control over the information that matters most. This is a direct consequence of the Signals Over Content principle — not an add-on feature.

Choosing a Deployment Model

Deployment models are not just infrastructure decisions. They determine where intelligence operates, where data resides, what information is shared and what remains local, and who retains governance responsibility.

Kaevor adapts to these requirements. Each deployment option preserves the same trust commitments while accommodating your organization’s specific governance posture, regulatory obligations, and risk tolerance.

Contextual intelligence should adapt to organizational trust. Not the other way around.