One governance substrate for every agent, harness, model, and tool.
Every proposal an agent makes - a prompt, a tool call, a payment - is routed through a typed governance pipeline, resolved in milliseconds, and written to a tamper-evident record before anything executes.
- Pipeline
Nine typed checks between intent and execution.
- Architecture
A governance substrate outside your runtime, one ingress, identical everywhere.
- Integrations
Govern every model and tool call with no code changes.
- Cognition
Governed loops, durable memory and model routing.
A new layer in the enterprise stack.
Building and launching an agent runtime or LLM-enabled application can be complex. But ensuring it behaves as expected is the real challenge.
Clinaro's Governance Substrate sits outside your application or agent runtime. Every action and every interaction with models, tools, data and memory passes through the same control layer.
It can approve, deny, pause, constrain, meter and audit execution, while preventing agents from expanding their own privileges.
The model is no longer the trusted decision-maker. It becomes a managed intelligence layer, governed by policy, fully observable and continuously accountable.
Enterprise grade control on any harness that you own.
Clinaro governance substrate sits outside third party harness, runtime or LLM, so the agent stack stays yours. Point any client, harness or workflow platform at the Clinaro Governance Substrate and it inherits identity, policy, capability scoping, budgets, audit, shared organisational memory and deterministic procedure apps.
- 01Identityactor: agent:analyst-07pass
- 02Authorizepolicy: dcm.read.tradespass
- 03Screenno injection · no PII in promptpass
- 04Budget$0.014 / 2,113 tokens · under cappass
- 05Approvalauto - within tenant guardrailpass
- 06Redact3 field masks appliedpass
- 07Capabilitytool library: postgres.read allow-listed for rolepass
- 08Accessscoped token minted · read-only · TTL 60spass
- 09Auditevt_9f81…c2 · signedpass
Nine typed checks between intent and execution.
An agent never acts directly. It proposes. The substrate resolves that proposal against identity, policy, content screening, budget, approval, redaction, capability scope and just-in-time access, then seals the result on a tamper-evident audit chain before anything is dispatched to an executor.
- Deterministic: the same intent under the same policy always resolves the same way.
- Fail-closed: a check that cannot pass stops the action, it does not soften it.
- Scoped: credentials are minted per action, read-only where possible, short TTL.
- Replayable: every decision, input and mask is reconstructable from the record.
Four tiers of memory, governed like any other action.
Clinaro memory is organised across two axes: tiers define scope, determining who memory belongs to across Agent, Team, Organisation and External Stores, while memory types define what is recalled, spanning procedural (how work runs), working (live context), episodic (past runs) and semantic (structured facts). Recall can recurse outward through authorised tiers, with every read, write and promotion passing through the Clinaro Governance Substrate, where access is scoped to the actor, policy-controlled, audited and metered against budget. Each tier can draw on internal and external vector, graph and document stores, all inheriting the same substrate-level controls.
Every run compounds enterprise knowledge with the record of how it was produced, so the substrate accumulates experience, not just data. Recall is recursive: rather than load a whole history into a context window, where accuracy rots as it fills, it reads only what each question needs, grounded and governed.
When you don't want an agent in the loop.
An agent in-the-loop decides each step at runtime, which is exactly what you want for novel or ambiguous work, and exactly what you don't want for critical, regulated or high-volume operations touching confidential data and services. Clinaro lets the model learn the process in-the-loop, then compiles the proven trace into a governed, deterministic application: one predictable call, versioned and audited, with scoped just-in-time access to secure tools. The agent stays at the edges, watching sources, structuring inputs and handling what the compiled path was never designed to resolve.
Feedback comes from exceptions. Anything outside the compiled envelope escalates back into the adaptive loop, the agent reasons it through, and where that response proves repeatable and safe it is tested, governed and folded into the next version. Over time the substrate accumulates a library of compiled loops, and expensive probabilistic reasoning is reserved for the cases that genuinely need it.
Learn in-the-loop · Run in compiled-loop · Govern everything
Every enterprise will run
thousands of autonomous workers.
They will either control them,
or they will not deploy them.
Enterprise briefings, technical deep-dives with the team, and evaluation deployments on request.
info@clinaro.com