Samay

Your Personal Guide to Sacred Wisdom

Samay

Your Personal Guide to Sacred Wisdom

Drishti

Your birth chart as a living map. Parashara and KP Jyotish in plain language. Your timing, your patterns, what this season of life is asking of you.

Viveka

All 18 chapters of the Gita as living counsel. Not recitation. A verse for what you are going through, right now.

Seva

Relationships, crossroads, grief, what comes next. Whatever brought you here, Samay meets you in it. In 22 languages. At any hour.

What brings people here

I keep making the same mistake. Why?

Karma & patterns

Is this the right time to act?

Muhurta & timing

My career feels stuck. What is my dharma?

Purpose & dasha

Are we right for each other?

Compatibility

I'm grieving and don't know what to hold onto.

Gita & loss

Something big is shifting. Should I act?

Transits & Prasna

I feel like I was meant for something more.

Life purpose

A question I can't ask anyone else.

Private counsel

I keep making the same mistake. Why?

Karma & patterns

Is this the right time to act?

Muhurta & timing

My career feels stuck. What is my dharma?

Purpose & dasha

Are we right for each other?

Compatibility

I'm grieving and don't know what to hold onto.

Gita & loss

Something big is shifting. Should I act?

Transits & Prasna

I feel like I was meant for something more.

Life purpose

A question I can't ask anyone else.

Private counsel

Samay Labs · Research Mission

Build Vedic
Superintelligence.

The largest knowledge system ever assembled by humanity has never been computationally formalised. Not meaningfully. Thirty million manuscripts. Four thousand years of continuous intellectual output. Texts that contain complete formal grammars, decision systems, cosmological models, and acoustic performance traditions. All of it sits outside the training distribution of every frontier model in existence.

This is not a content gap. It is a structural one. Current AI architectures are not built to reason over sutras, propagate commentarial lineage, or reconstruct oral knowledge from fragmentary transmission. We are building the systems that do.

30M+
Sanskrit manuscripts, most never digitised
196
Endangered Indian languages with active Vedic oral traditions
<50
Living Parashara-tradition Jyotishis fluent in all three major systems
The Problem

Current AI fails on Vedic knowledge in predictable, structural ways.

It is not that models haven't seen Vedic texts. Parts of Sanskrit corpora appear in Common Crawl. The Gita is in every training set. The failure is more fundamental: general-purpose language models lack the architectural commitments needed to reason reliably over symbolic systems that operate through strict rule hierarchies, lineage-dependent interpretation, and oral transmission with no written form.

Sutra systems are not retrievable by embedding similarity. Panini's Ashtadhyayi encodes grammar in 3,959 sutras that interact through a strict precedence hierarchy: metarules, context-sensitive overrides, and zero-context aphorisms that only resolve when the reader holds the entire system simultaneously. RAG over sutras produces fluent confabulation.
Commentarial knowledge is not additive. It is interpretive. Shankara, Ramanuja, and Madhva read identical Brahmasutra verses and reach opposite conclusions. The commentary is not a supplement to the root text. It is a competing world model. Current LLM architectures flatten this into averaging, which is wrong in every case.
Oral performative knowledge has no written proxy. The Dhrupad and Darbari Kanada of the Agra gharana exist only in performance lineage. A raga is not a scale. It is a formal constraint system specifying allowed ascent/descent phrases, characteristic gamakas, time-of-day applicability, and emotional flavour. None of this is recoverable from text.
Endangered languages are exiting without a machine-readable record. Tulu, Gondi, Nihali, Kodava Takk, and dozens of other languages carry Vedic oral traditions: ritual poetry, folk astronomy, medicinal plant knowledge. None of it exists in digitised form. Standard language model training requires tens of millions of tokens per language.
Domain evaluation does not exist. There is no benchmark for Jyotish accuracy, no eval suite for Gita interpretation quality, no automated way to tell whether a Vedic AI system is reasoning or hallucinating. We cannot improve what we cannot measure. We are building the evals simultaneously with the models.
Corpus construction is unsolved. Digitising Sanskrit manuscripts requires Devanagari OCR that handles scribal variation, regional scripts (Grantha, Sharada, Nandinagari), manuscript deterioration, and the absence of modern punctuation. Existing tools produce outputs that require expert correction at every line.
Architecture

Symbolic extraction plus neural synthesis, not fine-tuning or naive retrieval.

Wrong approach
Fine-tune a large model on Vedic text. Hope it learns the structure. Ship when it sounds confident enough.
Also wrong
Chunk texts into 512-token segments, embed them, retrieve by cosine similarity, and call it a Vedic AI.
Also wrong
Build a single general Vedic model. The domains are structurally different. Jyotish is a decision system. The Gita is hermeneutics. They require different architectures.
Our approach
Extract symbolic rules from sutras. Build domain-specific reasoning layers. Use neural synthesis only where formal structure ends. Keep commentary lineages separate and navigable.

The core architectural bet: Vedic knowledge systems are formal enough to be represented symbolically, but experiential enough to require neural completion at the edges. A Jyotishi does not retrieve. They reason from first principles, applying precedence rules to the specific configuration in front of them. The AI should do the same.

Case Study: Raga

Raga is not music. It is a constraint satisfaction system transmitted orally for three thousand years.

The Samaveda specified melodic contours for Vedic recitation before Greece had a musical notation system. What developed from that seed over three millennia is one of the most sophisticated formal constraint systems in any artistic tradition: 72 parent scales (melakarta), hundreds of derived ragas, each with mandatory ascent/descent phrases, permitted ornaments (gamaka), forbidden note combinations, time-of-day constraints (prahar), and associated emotional states (rasa) grounded in the Natyashastra's taxonomy of human experience.

The problem is not that this system is underdocumented. It is that the primary documentation is in performance. The Agra, Kirana, and Gwalior gharanas each hold subtly different interpretations of the same raga. These variations were passed guru-to-shishya in thousands of hours of oral instruction that never became text. When the last exponents of a rare raga perform their last concert, that version of the raga is gone.

We are building acoustic models that can extract the formal grammar of a raga from recordings, disambiguate gharana-specific interpretations, and represent the raga as a queryable constraint system.

Corpus

What we are building the knowledge base from.

JyotishBPHS · Saravali · Phala Deepika · Jataka Parijata · Uttara Kalamrita · Prashna MargaActive
Bhagavad Gita700 verses · Shankara, Ramanuja, Madhva, Tilak commentariesActive
SanskritPanini's Ashtadhyayi · Mahabhashya · Laghu Kaumudi · AmarakoshaBuilding
AyurvedaCharaka Samhita · Sushruta Samhita · Ashtanga HridayamBuilding
Upanishads10 principal Upanishads · Brahmasutra · major Vedanta commentariesBuilding
Natya + RagaNatyashastra · Sangita Ratnakar · gharana recordings (Agra, Kirana, Gwalior)Research
YogaYoga Sutras of Patanjali · Hatha Yoga Pradipika · Gheranda SamhitaPlanned
Vedic MathBharati Krishna Tirthaji's 16 sutras · Shulba SutrasPlanned
Endangered LanguagesTulu · Gondi · Nihali · Kodava Takk · Kurukh · Korku — oral corpus onlyResearch
"यद् भावो तद् भवति" — As the feeling, so becomes the reality.
The tradition understood that knowledge is inseparable from the mind that holds it. We are trying to encode not just the words, but the cognitive structure underneath them. — Bhagavad Gita 17.3
Open Research Problems

What we have not solved yet.

We are publishing these because they are genuinely hard, because we want collaborators who have thought about them, and because the field benefits from naming problems precisely.

Sutra-to-rule extraction. Formalising Panini's Ashtadhyayi as a computable rule system. Previous computational work (Akshar, SLP1) covers subsets. We need the full precedence hierarchy — utsarga (general), apavada (exception), and paribhasha (metarule) — encoded in a form that supports automated derivation verification.
Commentary-aware embeddings. Standard sentence embeddings treat Shankara's Advaita commentary and Madhva's Dvaita commentary on the same Brahmasutra verse as semantically similar, because the surface text is. They are philosophically opposite. We need embedding spaces that preserve doctrinal lineage as a first-class dimension.
Low-resource acoustic modelling for raga. Training phoneme-level ASR on endangered language oral traditions with under 100 hours of clean audio, no text transcripts, and multiple speaker-dialects. Standard self-supervised approaches (wav2vec 2.0, Whisper) require orders of magnitude more data per language.
Domain-specific evaluation. Building the first publicly available benchmarks for Jyotish reasoning accuracy, Vedic Sanskrit translation quality, and Ayurvedic diagnostic consistency. Without evals, progress is invisible and hallucination is indistinguishable from competence.
Multi-script manuscript digitisation. Devanagari OCR that handles Grantha, Sharada, Nandinagari, and Siddham scripts — with scribal variation, ligature ambiguity, and physical manuscript degradation — at accuracy levels that do not require expert correction on every line.
Jyotish chart reasoning. Formalising Parashari, KP, and Jaimini interpretation as a symbolic reasoning system with navigable precedence, planetary dignity tables, and dasha sub-period calculation that can be audited at each inference step. Not black-box prediction — explainable reasoning from first principles.

Join the Research.

We are looking for people who find these problems compelling — not because of the application layer, but because the problems themselves are interesting. You do not need to be Vedic-background. You need to be technically rigorous and willing to work at the intersection of traditions that have never been formalized computationally.

Write to us. Tell us what you're working on and why this matters to you.

NLP / LLM research Sanskrit computational linguistics Jyotish — advanced practitioners Vedanta scholars ASR / speech ML Ethnomusicology OCR / document AI Ayurveda researchers Indic language engineers Endangered language documentation Evaluation / benchmark design Institutional partners
ॐ

Pranava — the seed from which all knowledge unfolds.

The tradition has survived four thousand years of invasion, colonisation, and modernity. It does not need rescue. What is new is the possibility of preserving its formal structure at machine scale — not as a museum exhibit, but as a living reasoning system that continues to grow.

That is what we are building.

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