Creating an AI astrologer that interprets birth charts and delivers personalised Vedic guidance required solving unique NLP and knowledge representation challenges.
Vani AI is the conversational astrology engine powering the Staarvani platform. Building an AI that can discuss planetary positions, dasha periods, and life guidance with the depth of an experienced astrologer required solving technical challenges that standard chatbot frameworks do not address.
Knowledge Representation
Vedic astrology has a vast and interconnected knowledge base. A single planetary placement can have different interpretations depending on the house it occupies, the sign it is in, the aspects it receives from other planets, and the current dasha period. We built a structured knowledge graph that encodes these relationships, allowing Vani AI to reason about astrological principles rather than simply pattern-matching from a corpus of readings.
Personalisation at Scale
Every user has a unique birth chart, and their questions arise from their specific life context. Vani AI maintains a session context that includes the user's chart data, previous questions, and the current astrological transits affecting their chart. This allows follow-up conversations to build on previous interactions naturally. When a user asks "What about my career?", the system draws on their 10th house placement, relevant dasha, and current transits to provide a personalised response.
Multilingual Support
Astrology users in India communicate in Hindi, English, and various regional languages, often mixing languages within a single conversation. Our NLP pipeline handles code-switching natively, detecting language shifts and generating responses in the user's preferred language. Technical astrological terms are preserved in their traditional Sanskrit or Hindi forms where appropriate, maintaining authenticity.
The biggest lesson from building Vani AI is that domain-specific AI requires domain-specific engineering. Generic language models provide a strong foundation, but the real value comes from the specialised knowledge structures, validation rules, and conversational design that make the system genuinely useful to experts and beginners alike.
