Insights
Insights
Intelligence infrastructure for a more connected world. Company essays on institutional computing, AI workforces, digital twins, and governed intelligence. Organization blogs remain on each tenant host at /blog.
Articles
- AI and Intelligence Infrastructure
- AI Agents and Autonomous Work
- Digital Twins
- Institutional Computing
- Architecture and Engineering
- Security and Governance
- Product Updates
- Industry Perspectives
Institutional Computing
What is institutional computing?
Institutional computing is a shared, governed environment where an organization's people, records, agents, and twins can operate together — instead of across disconnected tools.
2026-10-26 · Sherivs
AI Agents and Autonomous Work
From AI assistants to coordinated AI workforces
A single assistant in a side panel cannot run an institution. Coordinated workers need identity, permissions, bounded tasks, and oversight.
2026-10-26 · Sherivs
Digital Twins
How digital twins maintain identity, state, and relationships
A twin that is only a 3D model is decoration. A useful twin remembers state, relationships, and events, then computes when those events occur.
2026-10-26 · Sherivs
Security and Governance
Designing AI systems with explicit permissions and verifiable outcomes
If an AI system cannot say who authorized an action, the action does not belong in an institution.
2026-10-26 · Sherivs
Architecture and Engineering
How event-driven computing reduces unnecessary persistent workloads
Always-on workers are an expensive default. Most institutional work is event-driven or scheduled.
2026-10-26 · Sherivs
AI and Intelligence Infrastructure
How Sherivs approaches connected institutional intelligence
Intelligence becomes useful when it is connected to authorized reality — and dangerous when it is not.
2026-10-26 · Sherivs
Industry Perspectives
Building governed intelligence for institutions
Intelligence that cannot be permissioned, recorded, and refused is not institutional infrastructure.
2026-10-26 · Sherivs
AI Agents and Autonomous Work
The difference between an AI agent and an autonomous engineering workforce
An agent completes a task. A workforce is a set of identities, permissions, and oversight. Treating them as the same thing is how systems lose control.
2026-10-26 · Sherivs