The vector database that can mathematically prove it never lost your data.
Q16.16 fixed-point arithmetic · BLAKE3 hash-chained audit log · openraft consensus · offline verifiable proofs
Every vector database makes a silent assumption: float arithmetic on one machine produces the same result on another. It does not. SIMD units, cloud hardware migrations, and IEEE 754 implementation variance mean replicas silently diverge — and you can never verify they haven't.
In AI systems this compounds: agent memory drifts between restarts, crash recovery is unverifiable, and an audit trail built on float results cannot be reproduced anywhere else.
Valori eliminates all of this with one decision: integer-only vector math, provably identical on every machine.
# State hash before a forced restart
curl $VALORI_URL/v1/proof/state
# → {"final_state_hash": [174, 163, 169, 225, 123, 111, 34, 11, ...]}
# kill -9 — no graceful shutdown, no flush
# State hash after automatic recovery
curl $VALORI_URL/v1/proof/state
# → {"final_state_hash": [174, 163, 169, 225, 123, 111, 34, 11, ...]}
# identical — bit-perfect recovery, cryptographically verifiedEvery byte of state is recovered from the append-only, BLAKE3-chained event log and verified against the pre-crash root. No data loss. No manual intervention. No trust required.
┌─────────────────────────────────────────────────────────────────────┐
│ Your AI Application │
│ LangChain · LlamaIndex · OpenAI Agents · Custom Orchestrators │
└────────────────────────┬────────────────────────────────────────────┘
│ Python SDK / HTTP / PyO3 FFI
┌────────────────────────▼────────────────────────────────────────────┐
│ VALORI │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │
│ │ Vector │ │ Knowledge │ │ Cryptographic │ │
│ │ Memory │ │ Graph │ │ Audit Trail │ │
│ │ (HNSW/Brute)│ │ (same store)│ │ (BLAKE3 + replay) │ │
│ └──────────────┘ └──────────────┘ └──────────────────────┘ │
│ ┌──────────────────────────────────────────────────────────────┐ │
│ │ Q16.16 Fixed-Point Kernel (no_std / no_alloc) │ │
│ │ bit-identical results on x86 · ARM · RISC-V · Cortex-M4 │ │
│ └──────────────────────────────────────────────────────────────┘ │
│ ┌───────────────────────┐ ┌──────────────────────────────────┐ │
│ │ Standalone Node │ │ 3- or 5-Node Raft Cluster │ │
│ └───────────────────────┘ └──────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
| Determinism | Q16.16 fixed-point — bit-identical across x86, ARM, RISC-V, Cortex-M4 |
| Audit trail | Append-only BLAKE3-chained event log; offline verifiable with no server |
| Tamper detection | Locates the exact altered event, byte offset, and commit timestamp |
| Raft cluster | 3/5-node consensus via openraft 0.9 + tonic/gRPC + mTLS |
| GraphRAG | Vector search + subgraph traversal in one call, one consistent snapshot |
| Agent memory (MCP) | valori-mcp — verifiable recall with BLAKE3 receipt; works with Claude Desktop |
| Recency decay | decay_half_life_secs fades older memories in ranking without touching the state hash |
| Self-maintaining memory | consolidate (supersede a memory) and contradict (flag conflicts) commit Supersedes/Contradicts edges to the audit chain |
| Multi-tenancy | Up to 1 024 named collections; per-tenant API keys with RBAC |
| Point-in-time reads | Replay to any past state hash or log index |
| GDPR erasure | Crypto-shredding — DEK destruction = O(1) erasure, audit chain stays intact |
| Embedded | no_std / no_alloc kernel; runs on microcontrollers with no heap |
| S3 offload | Snapshot archival + WAL rotation to S3/MinIO/R2 |
→ Full feature list and phase history
pip install valoricore
pip install "valoricore[local]" # + SentenceTransformer embeddingsfrom valoricore import MemoryClient
from valoricore.embeddings import SentenceTransformerEmbedder
embedder = SentenceTransformerEmbedder("all-MiniLM-L6-v2")
db = MemoryClient(path="./my_db", dim=384, index_kind="hnsw")
db.add_document(text="The patient presented with hypertension.", embed=embedder)
hits = db.semantic_search("blood pressure", embed=embedder, k=5)
print(db.get_state_hash()) # 64-char BLAKE3 hex — same on any machineVALORI_DIM=1536 \
VALORI_EVENT_LOG_PATH=./data/events.log \
VALORI_SNAPSHOT_PATH=./data/snapshot.bin \
cargo run --release -p valori-nodefrom valoricore import SyncRemoteClient
db = SyncRemoteClient("http://localhost:3000")
db.insert([0.1, 0.2, ...])
hits = db.search([0.1, 0.2, ...], k=5)
hits = db.search([0.1, 0.2, ...], k=5, decay_half_life_secs=86400) # recency-awarecargo install --path crates/valori-cli
valori setup # interactive wizard→ Cluster setup guide · Docker Compose · Helm chart · AWS/Azure Terraform
VALORI_URL=http://localhost:3000 valori-mcp{ "mcpServers": { "valori": {
"command": "valori-mcp",
"env": { "VALORI_URL": "http://localhost:3000" }
} } }cargo build --release --workspace
cargo test -p valori-kernel -p valori-node
cd python && pip install -e ".[dev]"Requires Rust stable. For Python FFI: cargo install maturin.
| Doc | What it covers |
|---|---|
| docs/getting-started.md | Full quickstart for all deployment modes |
| docs/api-reference.md | Complete HTTP API reference |
| docs/python-reference.md | Full Python SDK reference |
| docs/CLUSTER.md | Cluster setup, operations, failover |
| docs/DR.md | Backup, restore, cross-region DR runbook |
| docs/CAPACITY.md | Capacity planning — vectors/GB, WAL growth, S3 cost |
| docs/THREAT_MODEL.md | Security model and BLAKE3 MAC analysis |
| docs/DEPLOYMENT.md | Docker, Kubernetes, S3, Terraform |
| docs/authentication.md | API keys, RBAC, mTLS |
| docs/core-concepts.md | Fixed-point math, audit chain, determinism |
| docs/phases/README.md | Full build history and phase reports |
| benchmarks/RESULTS.md | Benchmarks and comparison vs Pinecone/Qdrant/Weaviate |
Paper: Valori: A Deterministic Memory Substrate for AI Systems
@article{gudur2025valori,
title = {Valori: A Deterministic Memory Substrate for AI Systems},
author = {Gudur, Varshith},
journal = {arXiv preprint arXiv:2512.22280},
year = {2025}
}Dual-licensed under MIT OR Apache-2.0 — free for commercial use.
Contact: varshith.gudur17@gmail.com
Built in Rust. Proven in production. Auditable by mathematics.
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