caura for the enterprise
The memory agents love.The control enterprises need.
Persistent, shared memory for fleets of AI agents. LLM-agnostic, harness-agnostic, provider-agnostic. Built with the visibility, isolation and audit the enterprise has to answer for.
Every point is a memory, placed by meaning. Brightness is recall.
Red halos are security findings, each tied to a memory, its writer and its scope.
Caura Prism: the console for visibility, cost, audit and the daily brief.
Everybody is building agents. Most demos never reach production.
Agents forget between sessions and repeat each other’s discoveries. Nobody can say what the fleet knows, or whether it is still true. Governed fleet memory is the missing layer between demo and production.
in production
eToro runs Caura as its company brain for 300+ agents.
One memory, shared across the fleet, inside one tenant.
Read the case study →The memory agents love.
Agents come and go. What they learn stays.
- PersistentLearned once, kept for every agent that follows.
- SharedEvery authorized agent in the tenant draws on one memory.
- CompoundingOutcomes tune recall; repeats crystallize into knowledge.
- Agent-nativeMCP, REST and Rail hooks. Usable on the first call.
The control enterprises need.
See everything. Decide who sees what.
- GovernedScope, trust and policy enforced inside the operation.
- IsolatedTenants isolate; fleets collaborate.
- AuditableEvery read, write and delete attributed and logged.
- VisibleWhat the fleet knows, who taught it, what it costs.
Enterprise agents are making decisions on knowledge nobody can see.
Six questions your stakeholders already ask. Caura Prism answers each one on a live map of the fleet's memory, and every answer ends in an action.
platform lead · field
“What does our fleet actually know?”
Coverage and gaps, visible at a glance.
pruneauditor · recall
“Why did the agent say that?”
Replay any recall, ranked and explained.
explainknowledge owner · evolve
“Is it still true?”
Contradictions and stale facts, surfaced for review.
resolvehead of ai · agents
“Are our agents sharing or siloed?”
Who wrote it, who recalled it, what never moved.
retuneciso · risk
“Is anything leaking?”
Every credential or PII finding, tied to a memory and its writer.
re-scopefinance · spend
“What does it cost?”
Tokens per memory, showback per agent.
tuneGovernance built in, not bolted on
Four boundaries. What the service enforces on every operation, and what it hands to agents.
- OrganizationOwnership, administration, compliance, billing. Operated through Prism.
- TenantThe hard isolation boundary. Memory never crosses tenants.
- FleetThe default collaboration boundary. Cross-fleet access needs explicit policy.
- AgentIdentity, attribution, permissions and trust level. Any framework plugs in.
On every operation
On every write
Ongoing, after the write
Delivered to agents
Governance ships in the Apache 2.0 core. Enterprise adds on-prem, air-gapped or white-label deployment, dedicated support with an SLA, and a dedicated account manager.
Models reason. Harnesses execute. Caura remembers. Prism controls.
Everything you already run stays on top. One governed memory goes underneath.
the memory loop
Why Caura is different
Six durable advantages. Everything else is evidence for one of these.
Any model, any harness, any provider. Apache 2.0 core.
Scope, trust, policy and audit enforced during the operation.
Contradictions surface, stale facts are superseded, history stays.
Outcomes tune recall per agent; repeats become knowledge.
Rail (preview) makes memory runtime behaviour, not a model decision.
Organization, tenant, fleet, agent. Policy, audit and spend on one console.
eToro runs Caura as its company brain for 300+ agents.
One memory, shared across the fleet, inside one tenant.
Read the case study →Accuracy scored by an LLM judge; savings against the full context; latency on a warm cache, single-tenant. Internally run, and single-agent memory only, not fleet sharing or governance. Your own corpus settles it. See the methodology →
Three ways to run the same engine
Same core, same APIs, same Prism console.
Apache 2.0. The full engine and governance. Five minutes from git clone to working memory.
github.com/caura-ai/caura →Nothing to run. Same APIs, same governance, SOC 2. Free tier to start.
Get started free →On-prem, air-gapped or white-label. Custom limits, dedicated support with an SLA, and a dedicated account manager.
Plan a pilot →Unlimited agents and fleets on every plan. Pay for what you store and recall. Free tier to start. See pricing →
Plan a fleet-memory pilot.
One workflow. Five to twenty agents. Two weeks. We measure four things: repeated failures avoided, knowledge reused across agents, permission correctness, and cost per completed task.
Agents are replaceable. Their memory is not.
info@caura.ai · caura.ai · github.com/caura-ai/caura