Bi-Temporal Knowledge Graph
Know what was true, when, and when you learned it.
Every node and edge tracks two timelines — valid time and transaction time. Time-travel any query. Causal-path discovery, counterfactual queries, microtheory scoping, Merkle provenance.
Capabilities
What it does.
Every capability is production-grade. No flags, no betas — these ship the day you adopt Minds.
Bi-temporal
Four timestamps per fact: t_valid_from, t_valid_to, t_created, t_expired.
Cypher-lite queries
Full temporal predicates: AS OF, BETWEEN, BEFORE.
Causal-path discovery
find_causal_paths() with confidence + provenance.
Counterfactual queries
What would be true if X were different?
Graph algorithms
PageRank, BFS, clustering — all operate over temporal slices.
Merkle provenance
Every edge anchored in a tamper-evident chain.
API
A few lines is all it takes.
The SDK reflects the conceptual model directly. No glue code, no orchestrator, no learning curve beyond the data shape.
exampletypescript
// Time-travel any query.
const alice = await minds.graph.getNode("alice@l1fe.ai", {
asOf: "2024-Q1",
});
// Find the causal chain.
const paths = await minds.graph.findCausalPaths({
from: "fact://q3-revenue-dip",
to: "fact://channel-mix-change",
maxHops: 4,
minConfidence: 0.7,
});Specs
What it costs, what it guarantees.
Performance
- Storage
- RocksDB-backed property graph
- Time model
- valid + transaction (4 timestamps)
- Traversal · 5-hop
- <100ms
- PageRank · 1M nodes
- <800ms
- Provenance
- BLAKE3 Merkle chain
Guarantees
- Durability
- fsync per WAL commit
- Isolation
- MVCC · snapshot
- Audit
- BLAKE3 Merkle chain
- Encryption
- AES-256-GCM per-namespace
- Concurrency
- 100K+ ops/sec
Build it on Minds.
Start with the SDK. Ship in an afternoon. Run anywhere — Akasha Cloud, on-prem, or air-gapped.