Academy Platform / academic lifeSystem / 01

Product

One platform for teaching, research, and collaboration.

ScienzaOS connects academic work through shared projects, sources, documents, review, approval, rights, and reuse. Research Agent for papers and funding proposals is the first offer on this foundation.

Research first
Sources stay visible
People retain approval
Designed for reuse
Institutional, partner, and public evidence streams converging into a governed research dossier
Evidence linkedReview accountableAction controlled
  1. 01Teaching
  2. 02Research
  3. 03Business
  4. 04Shared sources
  5. 05Human review
  6. 06Responsible reuse

Architecture overview

A layered system for governed research operations.

Stable objects connect people, roles, projects, sources, documents, versions, review, approval, rights, and reuse across the platform.

Review evidence governance
A layered scientific architecture model built from translucent domain and evidence planes
Architecture cutaway / domain contracts / governed state
01 / Experience layerAcademic projects · source library · review room · workflow surfaces
02 / Orchestration layerWorkflow engine · planning · drafting · review issues · approval state
03 / Intelligence layerRetrieval · grounded assistance · citation checks · consistency review
04 / Data and knowledge layerSources · documents · versions · rights context · reusable artifacts
05 / Runtime layerCapability routing · policy checks · adapters · sandboxed execution
06 / Infrastructure layerDatabase · object storage · outbox · keys · observability · recovery

Workflow primitives

Composable building blocks for every research process.

The same durable primitives connect Research Agent, Teaching Studio, and Business Collaboration through reviewed knowledge and responsible reuse.

Task

A bounded unit of work performed by a person, service, or controlled capability.

Plan

A structured sequence of steps, evidence requirements, gates, and accountable roles.

Tool

A replaceable capability invoked with explicit parameters and operating constraints.

Retrieval

Find and rank relevant evidence while preserving source and access context.

Evaluate

Assess quality, rights, policy, uncertainty, and decision readiness.

Decide

Issue a governed decision bound to exact evidence, criteria, authority, and conditions.

Adaptive runtime

Observe. Adapt. Execute with guardrails.

The runtime can refine plans and route capabilities while policy, decision state, and accountable human authority remain explicit.

A three-stage scientific instrument coordinating observation, adaptation, and controlled execution
Adaptive runtime / observe / adapt / execute

Observe

Collect evidence, case state, policy context, and outcome signals.

Adapt

Refine plans, capability choices, and next evidence within the approved boundary.

Execute

Run exact approved workflow steps and capture deterministic receipts.

Decision intelligence surfaces

Provider-neutral routing

Select an approved model, tool, data source, or human workflow according to purpose, quality, cost, latency, policy, and current availability.

01 / Approved capability set02 / Policy and purpose match03 / Recorded routing decision

Federated retrieval

Search institutional, partner, and public sources while preserving access decisions, citation, provenance, and freshness context.

Institutional sourcesPartner collectionsPublic literature

Evidence graph

Traverse relationships among entities, evidence, rights, methods, decisions, actions, and outcomes without replacing transactional records.

Claims linked to sourcesRights and method contextDecision-ready provenance

Institutional controls

Ready for accountable adoption.

Decision Ledger

Preserve the decision, rationale, evidence, authority, conditions, dissent, and outcome plan.

Human Approval Gates

Put qualified people at significant decision points and bind approval to exact payloads.

Release Gates

Require automated checks, quality thresholds, policy results, and operating readiness.

Enterprise Controls

Support identity, privacy, audit, observability, isolation, exports, and AI-off continuity.

Start with a real research workflow.

Evaluate one paper or funding-proposal workflow with a responsible reviewer, then expand only when the work proves useful.

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