ARA
Give AI systems a memory of every decision they make
ARA launched on July 16, 2026 with 8 votes, #2,235 of 24,623 launches that month and more than 90% of that year's launches.
What it does
AI systems make decisions, then forget everything: the exact inputs, the model version, the context. ARA is an infrastructure layer that records every decision your ML models make with the exact state that produced it, and can replay any of them months later. Incident debugging becomes a query. Drift shows up per entity. Training data joins without label leakage. Free Community Edition, runs entirely on your own infrastructure in under 10 minutes. SDKs on PyPI and Maven Central.
ARA: The decision data plane. Persistent entity intelligence at AI inference time. Built for the serving path.
ML systems decide. Then forget. ARA is the infrastructure layer that makes them remember, accurately, replayably, for every entity, at inference time. from ara_store import ARAStore store = ARAStore(host= "localhost" ) store.write(entity_id, features | decision, model_version= "fraud_v2.0" ) # the whole integration One write call in your serving path. Decision recorded, durable, tamper evident, replayable. pip install ara-labs-sdk · Java on Maven Central. Serving path Runs synchronously in your hot path. Not async. Not beside it. Exact replay Full entity snapshot per decision, not a log reconstruction. Immutable Append-only, cryptographically chained. Tamper-evident by design. Aug 2, 2026…from aralabs.ai
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