Parinita Almanac
The Sovereign Reference Layer
You consult the Almanac. You receive signed entries.
Almanac is the sovereign vector and retrieval-augmented generation layer. Its flagship workload is AI RAG — supplying signed entries to downstream models routed through Conduit. It is not competing on raw nearest-neighbor latency against Pinecone or Weaviate. It is competing on verifiable sovereignty.
RAG Has a Provenance Problem
Vector databases retrieve chunks and return them as context. No consultation produces a verifiable citation. No retrieval step has a compliance audit trail. Regulated AI deployments — ITAR research, clinical decision support, financial filings analysis, legal discovery — need every cited source to be admissible evidence.
Compliance teams cannot prove which source produced which AI output. Index residency requirements are not enforced at the storage layer. Cross-tenant index access is prevented only by policy, not by cryptography.
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No Retrieval Provenance
Vector databases return chunks. No consultation produces a verifiable citation. No retrieval audit trail. Compliance teams cannot prove which source produced which AI output.
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No Index Residency Enforcement
Vector index residency requirements are not enforced at the storage layer. Cross-jurisdiction index access is prevented only by policy, not by architecture.
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Cross-Tenant Index Risk
Tenant index separation enforced by policy, not cryptography. A misconfiguration exposes one tenant's corpus to another.
Signed entries. Chrysalis receipts. Four-layer isolation.
Almanac does not replace Pinecone, Weaviate, Qdrant, or Milvus for nearest-neighbor benchmarks. It wins on verifiable provenance per consultation — the compliance primitive that regulated AI deployments require.
Users do not query a database. They consult the Almanac. Results are signed entries with Chrysalis receipts anchored to the customer's 101-LLC jurisdictional entity.
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Signed Entries, Not Chunks
Results are signed entries with Chrysalis receipts anchored to the customer's 101-LLC jurisdictional entity. Every consultation is independently verifiable.
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Two Surfaces, One Engine
Almanac Search (retrieval API) and Almanac RAG (managed pipeline). Both produce signed entries and run on the same plane infrastructure.
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Anchored on Plane 4
In-memory index serving and search on Plane 4 (Intel Sierra Forest, 288 E-cores). Persistent indices and source corpora on Plane 5 (NVMe). Tracker agent is the consultation entry point.
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Four-Layer Tenant Isolation
Legal (101-LLC binding), network (Crucible per-packet identity), storage (per-tenant Plane 5 partition, jurisdiction-bound), cryptographic (HSM-signed receipts).
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Built for Compliance Retrieval
ITAR, HIPAA, and financial workloads where provenance is a compliance primitive — every consultation produces a cryptographic citation independently verifiable on Chrysalis.
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Post-Quantum Receipts
ML-DSA-65 (CRYSTALS-Dilithium, FIPS 204) for receipt signing on the roadmap. Multi-modal entries (image/audio/video) and federated cross-jurisdiction consultation coming Q4 2026.
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Tracker Agent
Consultation entry point. Classifies queries, selects retrieval strategy, coordinates reranking and prompt construction.
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Chrysalis Citation Chain
Every consultation receipt anchored on Chrysalis. Chain from source document to AI output is independently verifiable for any cited entry.
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Managed RAG Pipeline
Almanac RAG combines retrieval, reranking, prompt construction, and synthesis through Conduit in one managed pipeline — no per-product RAG reinvention.
The Plane Model
Orchestra introduces "planes" — logical groupings of hardware optimized for a specific workload class. Unlike Kubernetes node pools, planes represent fundamentally different hardware architectures with different drivers, network requirements, and scheduling semantics.
The plane model is what makes Orchestra different from every other orchestration tool. Kubernetes sees nodes. Orchestra sees purpose-built hardware tiers and routes workloads accordingly.
Search. Rerank. Construct. Synthesize. Sign.
Every consultation traverses the Tracker agent, retrieves from Plane 4 in-memory index, reranks, constructs a prompt, routes synthesis through Conduit, and returns a signed entry with a Chrysalis receipt. The receipt is independently verifiable on Chrysalis.
- 01Query ClassificationWhat is the query type and corpus? Which retrieval strategy applies?
- 02Sovereignty CheckWhich corpus partitions is this tenant authorized to access? Jurisdiction-bound?
- 03In-Memory Index SearchSearch Plane 4 (Intel Sierra Forest) in-memory index. Return candidate entries.
- 04RerankingRerank candidates by relevance and provenance quality. Select top entries for prompt construction.
- 05Prompt ConstructionConstruct retrieval-augmented prompt with selected entries as signed citations.
- 06Conduit SynthesisRoute prompt to Conduit for multi-model synthesis. Apply sovereignty parameter.
- 07Entry SigningSign the consultation result with HSM-backed keys. Generate Chrysalis receipt.
- 08Chrysalis AnchoringAnchor receipt to Chrysalis on the customer's 101-LLC jurisdictional entity. Return signed entry to caller.
import almanac
client = almanac.Client(seat_id='seat_8f3k2...', jurisdiction='us-east')
result = client.consult(query='ITAR classification criteria for dual-use components', corpus='itar-library-2026', sovereignty='sovereign')
print(result.signed_entry, result.chrysalis_receipt)Proven at scale. Not in a lab.
Parinita AI Edge is the production deployment of the Parinita platform and the largest heterogeneous AI infrastructure deployment in the United States.
Parinita AI Edge
The most complex heterogeneous AI infrastructure in the United States. 101 sites, 9 planes, 12,000+ nodes, 4 accelerator vendors, dual network fabrics, four-layer tenant isolation — all through a single sovereign control plane.
Network & Security Infrastructure
- Multi-vendor acceleratorsFour accelerator vendors — Intel Habana, NVIDIA, AMD, Qualcomm — orchestrated through one control plane with unified scheduling, monitoring, and lifecycle management.
- Dual-fabric networkingCisco production fabric and Arista GPU backend fabric operating as a coordinated system, bridged by identity-aware routing.
- Nationwide scale101 sites across 42 U.S. states, each operating autonomously with a local control agent and a sovereign cross-site routing plane.
- Multi-tenant isolationFour-layer defense-in-depth: VXLAN VNIs, identity-routing, Palo Alto firewalls, and Cilium eBPF — validated across every plane and site.
- Compliance readinessFIPS 140-2 at launch, with FedRAMP Moderate, CJIS, and IL4/IL5 certification paths active through Parinita compliance profiles.
- Sub-millisecond routingEvery request classified and dispatched in under 1ms, enabling real-time SLA enforcement without perceptible overhead.
Built for regulated AI retrieval.
Almanac does not ask you to migrate your vector database. It is the compliance retrieval layer for workloads where provenance is a compliance primitive — layered above your existing corpus.
ITAR research, clinical decision support, financial filings analysis, and legal discovery — any regulated workload where every cited source must be admissible evidence and every retrieval step must have a cryptographic audit trail.
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ITAR Research RAG
AI-assisted research across ITAR-classified corpora where every retrieved citation must be admissible and every retrieval step must have a cryptographic audit trail.
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Clinical Decision Support
Healthcare RAG where every source cited in an AI recommendation must have HIPAA-compliant provenance and FDA 21 CFR Part 11 audit trail.
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Financial Filings Analysis
SEC, FINRA, and SOX-bound financial analysis where every source cited in an AI output must be independently verifiable with blockchain-anchored provenance.
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Legal Discovery
E-discovery RAG where every retrieved document must have a court-admissible chain of custody from source to AI-assisted analysis.
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Multi-Jurisdiction RAG Operations
Organizations with vector indices carrying jurisdiction-specific residency requirements. Almanac enforces residency at the storage layer, not just in policy.
Surface Options
Almanac exposes two surfaces: Almanac Search for teams building their own RAG pipelines, and Almanac RAG for the fully managed retrieval-to-synthesis pipeline.
Lower-level retrieval API — signed entries and Chrysalis receipts, plugs into existing RAG pipeline | Best for: Teams with existing RAG infrastructure
Fully managed RAG pipeline — retrieval, reranking, prompt construction, Conduit synthesis | Best for: Teams building compliance-bound AI applications
Custom corpus ingestion, multi-jurisdiction index partitioning, post-quantum ML-DSA-65 receipts | Best for: Regulated enterprises with complex corpus requirements
Request a Demo
Our engineering team has deployed Almanac as the sovereign reference layer across 101 sites. We bring that operational experience to every deployment conversation.