When this approach fits your task.
You want long-running AI employees that live in Slack, Teams or WhatsApp and can receive dedicated cloud compute.
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Cloud AI workforce
NinjaTech vs Laryaa
24/7 AI employees on dedicated cloud machines, with team-channel access, broad integrations and deployment choices.
Laryaa architectural assessment · reviewed 26 August 2026
What it is
NinjaTech in one decision frame.
24/7 AI employees on dedicated cloud machines, with team-channel access, broad integrations and deployment choices.
Where it is strong
- Dedicated isolated cloud VM per AI employee, according to NinjaTech
- Long-running work and collaboration from team messaging channels
- Model choice, BYOK and customer-cloud/VPC or data-centre options are publicly described
Readiness matters: the Laryaa column includes architectural intent and deployment-specific capabilities. It is not a claim that every listed capability is generally available. Check the capability register and validate the other product’s current configuration. Source review date: 26 August 2026.
Architecture matrix
Follow the work, data and proof.
| Architectural question | NinjaTech | Laryaa |
|---|---|---|
| Primary execution | Dedicated cloud VM per employee; vendor describes customer-cloud options | Supported responsibility paths on controlled endpoints |
| Data path | Connected tools, browser state and team-channel context | Protected context remains local/private where supported; only the necessary request crosses boundaries |
| Intelligence choice | Frontier and open models; model choice and BYOK documented | Model-independent policy: local/private intelligence where suitable, frontier selectively |
| Deployment | Managed SaaS, customer cloud/VPC/data centre and vendor-described air-gapped option | Local, edge, VPC, private or other customer-controlled options where supported |
| Metering | Credits for managed service; enterprise deployment described as unmetered | Designed to reduce repeated frontier inference and avoid a cloud computer for every task |
| Controls | Approvals, scoped permissions and enterprise administration | Responsibility policy, application permissions, review points and surfaced exceptions |
| Completion evidence | Thread-visible actions and finished work | Inspectable deliverable, changed records, evidence and exceptions |
The architectural question
Does the organisation want managed cloud employees, customer-cloud/VPC deployment, or a system that keeps more execution on existing endpoints?
Where Laryaa differs
What to evaluate with Laryaa.
- Laryaa is designed to use existing supported endpoints first instead of assigning a cloud computer to every responsibility.
- It minimises routine frontier usage through known work paths and selective judgement calls.
- Air-gapped, perimeter and training-use statements remain vendor claims that buyers should validate for their exact deployment.
Decision guide
Choose the architecture that fits the responsibility.
When deployment and review requirements matter.
Choose Laryaa when supported work should stay near existing systems, protected context should be minimised, and completion needs an inspectable deliverable or exception trail.
Get guidance →Evidence discipline
First-party sources.
Reviewed 26 August 2026. This page is Laryaa’s architectural assessment based on current first-party public documentation. Product capabilities, previews, editions and deployments change; validate the exact configuration with each provider.
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