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Sikkanam
AI-Powered Tamil Nadu Travel Planner & Budget Guide
Sikkanam is an AI-powered travel planner built for Tamil Nadu. It helps travelers discover destinations, generate day-wise itineraries, estimate trip budgets, explore hotels, and plan routes with greater transparency. Unlike generic travel tools, Sikkanam combines destination intelligence, budget planning, route guidance, and an AI travel assistant in one platform. Whether you're planning a weekend getaway or a multi-city trip, Sikkanam helps you travel smarter, spend better, and explore more.
Hey hunters! 👋
Thank you so much for checking out the launch of Sikkanam! 🎒🗺️
💡 The Inspiration
The inspiration for Sikkanam came from a common frustration: trying to use popular AI tools to plan a budget trip. The AI would construct beautiful stories, but when it came to numbers, it completely fell apart—recommending expensive 1st AC sleeper train classes for a tight ₹5,000 budget, hallucinating non-existent bus routes, or claiming a 500 km journey only takes 3 hours.
Budget travel requires strict, realistic parameters. If a travel budget is based on guessed numbers, the trip falls apart.
❌ The Problem We're Solving
AI hallucination in travel logistics. We wanted to build a planner that guarantees 100% cost transparency and geographic accuracy. We wanted a tool that actually knows that:
Trains from Chennai to Salem or Coimbatore take 5–8 hours (not 3).
The Nilgiri Toy Train runs once a day at 7:10 AM, and TNSTC buses are the primary budget-friendly backup.
Regional food recommendations should be authentic and verified rather than guessed.
⚙️ How Our Approach Evolved
We initially started with a standard LLM chatbot, but quickly realized that generative AI is inherently bad at strict math and real-time transit timetables.
To solve this, we pivoted to a hybrid architecture:
The Deterministic Cost Engine: We built a local rule engine that handles all calculations (transit fares, room occupancy splits, entry fees) mathematically. The AI is strictly barred from estimating costs.
Official Brochure RAG: We parsed the official Tamil Nadu Tourism Department brochures (Heritage, Beach, Ecotourism, and Culinary guides) into a structured JSON database. The AI Companion uses this to retrieve authentic spots (like Tada Falls hikes or Manapparai Murukku origins) and feeds it directly to the user.
Dual API Fallback & Cache: We wrapped our API in a dual-LLM fallback (Groq Llama 3.1 + Gemini 1.5 Flash) and pre-seeded local caches to make home-page queries load instantly (0ms latency) and survive rate limits.
We'd love to hear your feedback on the planning engine! Let us know what destination you'd plan next! 🚀
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About Sikkanam on Product Hunt
“AI-Powered Tamil Nadu Travel Planner & Budget Guide”
Sikkanam was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #156 on the daily leaderboard. Sikkanam is an AI-powered travel planner built for Tamil Nadu. It helps travelers discover destinations, generate day-wise itineraries, estimate trip budgets, explore hotels, and plan routes with greater transparency. Unlike generic travel tools, Sikkanam combines destination intelligence, budget planning, route guidance, and an AI travel assistant in one platform. Whether you're planning a weekend getaway or a multi-city trip, Sikkanam helps you travel smarter, spend better, and explore more.
Sikkanam was featured in Productivity (655.7k followers), Developer Tools (515.5k followers) and Artificial Intelligence (473.1k followers) on Product Hunt. Together, these topics include over 325.2k products, making this a competitive space to launch in.
Who hunted Sikkanam?
Sikkanam was hunted by Pranavesh Nandakumar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Pranavesh Nandakumar