OLAV v0.10.0 — Open Source Launch
OLAV is now publicly available under BSL-1.1. Here's what's inside the platform, how the architecture works, and what comes next.
We’re open
After months of internal development, OLAV v0.10.0 is now publicly available under BSL-1.1.
The full platform core — CLI, agent runtime, audit chain, API registry, and Creator Agent — is open and free to self-host.
How it works
OLAV sits between your team and your infrastructure APIs. Every operation flows through four governance layers before execution:
graph TD
U[User / CLI] --> AAA[Layer 0 — AAA\nAuthN · AuthZ · Audit]
AAA --> MW[Layer 1 — Middleware\nCache · Rate-limit · Retry]
MW --> SB[Layer 2 — Sandbox\nSchema validation · Dry-run]
SB --> OUT[Layer 3 — Output\nNormalise · Sign · Emit]
OUT --> API[Downstream API]
style AAA fill:#7f1d1d,color:#fca5a5,stroke:#991b1b
style MW fill:#78350f,color:#fcd34d,stroke:#92400e
style SB fill:#14532d,color:#86efac,stroke:#166534
style OUT fill:#1e3a5f,color:#93c5fd,stroke:#1d4ed8
No operation bypasses this chain. The audit record is written before execution and is immutable.
Creator Agent — registering new API skills
When you point OLAV at a new API, the Creator Agent walks through six deterministic steps to produce a deployable skill:
sequenceDiagram
actor Dev as Developer
participant CA as Creator Agent
participant DB as DuckDB Registry
participant API as Target API
Dev->>CA: Register skill (OpenAPI schema)
CA->>CA: Parse & validate schema
CA->>API: Probe endpoints (dry-run)
CA->>DB: Store skill + constraints
CA->>CA: Generate semantic embedding
DB-->>Dev: Skill ready ✓
The result is a callable, audited, semantically-indexed skill — no custom glue code required.
Self-evolution loop
OLAV learns from failures. When an agent operation hits a constraint violation, the failure pattern is absorbed as a new rule and immediately applied to future queries:
flowchart LR
Q[Query] --> M{Match in\nsemantic cache?}
M -- Hit --> R[Return cached result]
M -- Miss --> A[Agent execution]
A --> V{Constraint\ncheck}
V -- Pass --> O[Execute + Audit]
V -- Fail --> E[Extract failure pattern]
E --> C[Emit new constraint rule]
C --> M
Over time, the constraint ruleset grows, and repeated failure patterns vanish.
Performance
The semantic cache gives dramatic speedups for repeated or paraphrased queries:
| Query type | Latency |
|---|---|
| Exact cache hit | < 1 ms |
| Semantic cache hit | ~5 ms |
| Full agent execution | 800 ms – 2 s |
| Cache hit vs full exec | 2000× faster |
What’s next
- v0.11 — Multi-agent orchestration, shared memory bus, parallel execution DAG
- v0.12 — Enterprise auth integrations (OIDC, SAML, LDAP)
- OLAV Cloud — Managed hosted option, waitlist opening soon