Every agent remembers differently
Private per-agent context produces silos. Teams need shared evidence that survives tool and model changes.
Typed evidence infrastructure
Ontic Fabric gives people, agents, and auditors one governed substrate for knowledge: typed ontologies, provenance-bearing evidence, durable work streams, and document and audio transduction.
Models, tools, and sessions are replaceable. Decisions, obligations, code, documents, and evidence remain addressable in your substrate.
The enterprise problem
When agents write code, review contracts, resolve incidents, and summarize decisions, their work creates organizational knowledge. If that knowledge lives only in chats, tickets, or private sessions, it disappears when the session ends.
Private per-agent context produces silos. Teams need shared evidence that survives tool and model changes.
An answer needs a source, a time, and a type. Ontic Fabric preserves provenance and graph relationships instead of loose summaries.
Intent, dependencies, approvals, validation, and outcomes become typed records that the next agent—or auditor—can traverse.
The substrate
Ontic Fabric is not another workspace application. It is the memory and evidence layer underneath the tools your organization already runs.
# one substrate, several typed domains legal.obligation ob-104 └─ satisfied_by ─▶ service svc-auth service svc-auth ├─ implemented_by ─▶ repository repo-identity └─ changed_by ─▶ work_item work-8841 work_item work-8841 ├─ validated_by ─▶ test_run run-2026-11-13 └─ approved_by ─▶ reviewer security-team
Governed work streams
Ontic Fabric represents work as a typed graph: intent, dependencies, assignments, evidence, reviews, and outcomes. Humans keep approval authority while agents execute against explicit scope.
Define the outcome, constraints, owners, and acceptance evidence before dispatching expensive work.
Agents, repositories, documents, and validation results remain linked instead of scattered across logs.
Reviews reference tests, deployments, approvals, and source evidence—not unsupported claims.
Reusable skills and session fossils carry forward what worked, with provenance back to the originating work.
Empirical evolution
A lane combines a scope, ontology, skill set, model policy, context budget, and evaluation set. Benchmarked lane versions make agent operations improvable rather than anecdotal.
Sessions, work items, reviews, and outcomes become substrate records.
Measure task success, evidence quality, review load, inference usage, and escaped defects.
Promote skills, fossils, and lane definitions with their evaluation provenance.
Deployment
The same substrate runs on an individual workstation, an isolated managed workspace, or an enterprise-controlled deployment.
Run the substrate on hardware you control, with exportable content and no mandatory cloud dependency.
An isolated workspace with deployment, upgrades, backups, drift monitoring, and support.
Bring your own cloud or use an isolated managed tenant, with governance and audit controls matched to the engagement.
Assurance
We will publish the evidence buyers need to evaluate the substrate rather than asking them to accept adjectives.
| Commitment | What we will publish | Status |
|---|---|---|
| Retrieval quality | Reproducible recall and typed-evidence benchmark results, including baseline comparisons. | In preparation |
| Transduction | Supported format matrix with fidelity, provenance behavior, latency, resources, and cost. | In preparation |
| Security assurance | SOC 2 / ISO 27001 readiness scope and report status when issued. | Roadmap |
| Operations | Backup and restore drills, upgrade policy, incident history, and service limits. | Pilot documentation |
Closed pilots
Pilots start with a bounded corpus, explicit acceptance evidence, and measured retrieval and transduction results. No public claims are made from your data.