The operating system for high-trust autonomy.
Clinaro is the universal enterprise harness for high-trust AI agents: one self-hosted control substrate to integrate, monitor and manage agents for regulated operations, critical infrastructure, and sensitive data handling. Every action is owned by a human and crosses a typed governance pipeline before it ever touches a model, tool, database or a dollar.
- 1exposed port
- the entire substrate presents a single network ingress; every service behind it is unreachable except through governance
- 9checks per action
- identity, authority, screening, budget, approval, redaction, capability, access and audit - enforced independently of the agent, on every action
- 7ms median decision
- typical governance decision measured from the live audit stream; even the slowest 5% complete in under 40ms - too fast for a user or an agent to feel
- 100%on record
- every prompt, tool call and approval is written to a tamper-evident audit chain, so any action can be replayed and evidenced after the fact
Authenticated is not safe.
Enterprise security was built around identity and access control for deterministic software. Agents reason and act at runtime, so those controls alone cannot establish trust.
Roles, tokens and ACLs prove an agent is authenticated. They cannot say what it will do next. A fully credentialed agent can read a thousand records, write messages and send emails - without breaking a single access rule. The path from a natural-language request to a privileged system action is dangerously short: no policy check, no approval gate, no cost control, often no audit record.
Data exfiltration
Confidential documents sent verbatim to a public cloud LLM. No record it ever left the tenant.
Cost overrun
Every trivial request routed to expensive frontier models. Budgets discovered at invoice time.
Injection → execution
Instructions embedded in chats and documents become unauthorised privileged actions.
Rogue usage
Sensitive data, tools and services accessed and used in unapproved ways by credentialed agents.
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 Enterprise Harness 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.
One harness for every
agent, 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 harness 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.
- 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 harness 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.
Enterprise grade control on any agent that you own.
Clinaro sits outside third party runtimes or LLMs, so the agent stack stays yours. Point any client, framework or workflow platform at the Clinaro harness and it inherits identity, policy, capability scoping, budgets, audit and shared organisational memory with no code changes.
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 Harness, 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