The Full Roadmap

Vision & scope

SarvaVeda is a self-hosted foundation platform that encodes, reasons over, and generates from the entirety of the Sanātana Dharma textual universe — grounded in the received text, validated by scholars, and owned by the institution.

The knowledge universe — four concentric layers

• Core canonical texts — the four Vedas in Padapāṭha and Saṃhitāpāṭha; the Brāhmaṇas, Āraṇyakas and Upaniṣads; the Śrauta and Gṛhya Sūtras; the Prātiśākhyas. ~100,000 pages of primary text with traditional bhāṣya.
• The complete Ṣaḍaṅga — all six Vedāṅgas in full (Śikṣā, Vyākaraṇa, Chandas, Nirukta, Jyotiṣa, Kalpa), the four Kalpa-sūtra classes (Śrauta, Gṛhya, Dharma, Śulba), and the Upāṅgas. ~100,000 further pages.
• The complete Purāṇa corpus — all 18 Mahāpurāṇas and the principal Upapurāṇas, segmented to adhyāya and śloka, with khaṇḍa/saṃhitā structure.
• Stotra & ancillary — the full Stotra literature; Itihāsa, Āgama and Upaveda texts; and the 2,000-topic Swadharma encyclopaedia. ~1 million pages overall, plus 1,000 hours of recitation and lecture video.

Eight functional objectives

• 1 — Complete knowledge store: all Veda, Śāstra and Purāṇa, retrievable to the Ṛk / unit / pada level.
• 2 — Canonical input processing through the MAP (Meaning–Analysis–Presentation) pipeline.
• 3 — Grammar-aware display: Pāṇinian analysis on hover, without disrupting the reading.
• 4 — Layered delivery: mūla, Padapāṭha, Bhāṣyam and meaning together, with linked passages.
• 5 — Semantic interlinking: a knowledge graph of intertextual relationships.
• 6 — Multilingual generation: Sanskrit, Hindi, Telugu, Kannada, English.
• 7 — Cross-disciplinary annotation: bridges to science, mathematics, philosophy and the arts.
• 8 — Ritual generation: Śrauta Prayoga, the eight Vikṛti forms, and Sāma renderings.

Hardware architecture

Self-hosted on two GPU servers at VVV Mysore — full data sovereignty over the sacred corpus, operating as a primary-training plus inference/validation cluster.

Corpus assembly & data pipeline

Four trust tiers

All training data is classified by trust, which governs its weight during fine-tuning.

Existing holdings — the seed corpus

SGSP already holds a substantial digitised collection, in two processing tracks:

• Track A — Unicode DOCX (immediate): ~30 files including the complete classical Śrauta register (11 Śrauta Sūtras) and 8+ Gṛhya Sūtras; commentated editions that supply mūla↔bhāṣya alignment pairs; and MAP-format exemplars that serve as the gold output templates the model learns from.
• Track B — scanned library (OCR): hundreds of critical and commentary editions across the śāstra spectrum — an estimated 100,000–200,000 pages.

The seven-stage industrial OCR pipeline

• O1 Intake & triage — every book logged in a digitisation ledger (edition, script, layout class, scan grade).
• O2 Preprocessing — deskew, dewarp, denoise, binarise, split spreads.
• O3 Layout analysis — classify zones (mūla, commentary, footnote, apparatus) so text is never read across columns.
• O4 Script-aware OCR — the best engine per script (Devanagari, Grantha, Telugu, Kannada, Roman-IAST), recorded per book.
• O5 Vedic svara recovery — accent marks (which generic OCR silently drops) detected as graphical objects and re-inserted, or transferred from a verified source.
• O6 Lexicon-guided post-correction — the Vyākaraṇa FST doubles as the most complete Sanskrit spell-checker ever built, flagging any non-analysable form.
• O7 Scholar quality gate — 10% sample graded per book; anything below 98% akṣara accuracy loops back. Accepted text is committed with full provenance.

Text preparation & the citation principle

Every document also passes a seven-stage preparation flow — ingest → normalise → segment → align → annotate → knowledge-graph → quality-gate — with text preserved exactly, including VijayaDV PUA and Vedic accents. A citation extractor parses all 72 volumes to compile the register of every text the Series quotes, guaranteeing the corpus covers the sources the model is most often asked about.

Model architecture & training

Rather than training from scratch, SarvaVeda uses retrieval-augmented generation plus domain fine-tuning — the right instrument for a high-precision, fidelity-first domain.

• Base model: Llama 3.1 70B or Mistral Large 2 (128k context); Gemma 2 27B as a lighter alternative.
• Fine-tuning: QLoRA with 4-bit NF4 quantisation for training, 8-bit for inference.
• Retrieval: a vector database over the full corpus grounds every generation in retrieved source passages.

The MAP pipeline

Every query passes through Meaning-retrieval (semantic match of the top passages), Analysis (grammar + knowledge graph), and Presentation (the model assembles a layered, mode-appropriate response).

Nine specialised engines

• Śrauta Prayoga — complete rite sequences with mantra, svara and ṛtvij assignment; every step citing its sūtra.
• Sāmaveda Stotra — stotra assembly (stotriyā, viṣṭuti, stobha) for a given Soma rite, in traditional notation.
• Vikṛti Pāṭha — all eight forms (Jaṭā, Ghana, …) with correct sandhi and svara at every junctura.
• Tarka sentence structure — formal pañcāvayava and Navya-Nyāya analysis; powers śāstrārtha reasoning.
• Varṇa Krama — akṣara-by-akṣara decomposition with per-syllable svara and mātrā.
• Sāma Sound Analysis (audio) — pitch/svara extraction (CREPE / wav2vec 2.0) → automatic notation → Ūha re-framing onto new chandas.
• Vyākaraṇa vocabulary engine — a rule-based Pāṇinian generator producing the full derived lexicon (>100 million forms) in a finite-state transducer, each form carrying its prakriyā.
• Nirukta etymology — Yāska-style nirvacana with the Pāṇinian vyutpatti shown alongside, context-resolved for polysemy.
• Chatur-Darśana engine — one sentence interpreted in parallel through Tarka, Vyākaraṇa, Mīmāṃsā and Vedānta, with a synthesis of where they converge and differ (e.g. svargakāmo yajeta).

Multilingual generation

Six languages in Phase 1 (Sanskrit, Hindi, Telugu, Kannada, English, plus IAST). All meaning is generated from Sanskrit as the pivot, then translated — so the tradition's semantic precision is never lost to a direct-to-English rendering.

Application layer

Stack: React + TypeScript + Tailwind frontend; FastAPI backend; Qdrant (vectors); Neo4j (knowledge graph); vLLM / Ollama serving; Keycloak (role-based access); Typesense (lexical search).

The layered reader

• Level 1 (always visible): Devanagari mūla + IAST + English meaning.
• Level 2: Padapāṭha with word-by-word breakdown.
• Level 3: Bhāṣyam excerpt with translation.
• Level 4 (hover any word): dhātu, pratyaya, vibhakti, Pāṇini-sūtra reference — pre-computed, sub-100 ms, no model call.
• Level 5 (sidebar): related mantras, Brāhmaṇa passages, connected Śāstra episodes and Purāṇa parallels from the knowledge graph.

Scholar workbenches

Dedicated interfaces for Prayoga generation, the Vikṛti generator, the Sāma Studio (stotra + sound analysis + Ūha workbench), the Tarka Workbench and Varṇa-Krama viewer, the four-column Chatur-Darśana view, the Stotra Library and Nirukta Explorer, and cross-disciplinary notes.

Phased implementation — ~30–36 months

Team & governance

Roles

• Principal Investigator — overall vision, corpus authority, Śrauta ritual validation.
• Technical Director (AI/ML) — architecture and delivery (recruiting).
• Vedic NLP Lead — Pāṇinian grammar annotation design; mūla↔bhāṣya alignment.
• Sāmaveda & Prayoga Lead — Sāma training data and Prayoga validation.
• Data Pipeline Engineer — ingestion, embeddings, training infrastructure (recruiting).
• OCR Pipeline Operator — the industrial digitisation programme (recruiting).
• Frontend Developer — the reader and workbenches, with Indic-script rendering (recruiting).
• Scholar Review Panel — 4–6 VVV/SVAMI faculty validating data and grading outputs.
• Institutional Advisor — fundraising and diaspora partnerships.

Ownership & licence

SarvaVeda is a project of Sanatana Guru Sampradaya Pratishthanam (SGSP), Mysore. All model weights, training data and code are the intellectual property of SGSP. The foundation model will be released under a restricted, non-commercial research licence for accredited Vedic institutions and universities. Dharma Poshanam Inc. (USA 501(c)(3)) is the vehicle for tax-deductible international support.

Risks & mitigations