Abhinav Mishra

A

Meeting

  • 2m

new event type

  • 15m

new event type 22

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new meeting 123

  • 2m

hello 123

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hello 123 meeting

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hello 456 meeting

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me 5

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me 7

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me 8

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new event 123123123

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managed event 2

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helllo 123

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$20.00

order-feature

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helllo 123

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$20.00

testing 5678

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asdfsadf

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  • About Company

    Lunacal.ai builds a modern scheduling product that turns a simple booking link into a high-converting, story-driven scheduling page šŸŽÆ. Instead of sending prospects to a plain, forgettable calendar screen, we help teams create a page that feels personal and branded—complete with context like product images, videos, testimonials, and even personal photos—so visitors understand who they’re booking with and why it matters.

    Our core value is improving first impressions and reducing drop-offs before a meeting is booked šŸš€. Behind the scenes, we’re not just designing pages—we’re building a reliable scheduling stack with strong infrastructure for safe rollouts, testing/CI, messaging workflows, and automation. The result is a smoother booking experience that starts conversations warmer, with better context, and helps convert more prospects into real calls.

    What We Do

    FAQs

  • Riya Kapoor

    Growth Lead, B2B Studio Labs

    We switched to Lunacal.ai to make booking links feel less generic, and it immediately improved the quality of inbound calls. Prospects came in with more context because the page told our story and showed proof. Setup was quick, and the experience feels genuinely branded.

    TestimonialsImage
    Testimonials
  • About me

    I’m Abhinav Mishra, a full-stack engineer focused on building TypeScript products and dependable backend systems. Right now, I’m a Software Developer Intern at Lunacal.ai, where I work across the scheduling product’s infrastructure and platform foundations—things like rollout controls, testing/CI, SMS workflows, AI meeting orchestration, and automation for custom domain provisioning. I enjoy working close to the core of a product: the parts that users don’t always see, but that determine whether the experience feels fast, safe, and trustworthy.

    In parallel, I’ve been building and experimenting with AI-powered features end-to-end—LLM workflows, speech-to-text (STT), text-to-speech (TTS), and intelligent search systems. My approach is pragmatic: I care about speed and clean implementation, but I’m equally serious about reliability, observability, and reducing edge-case failures. I like shipping features that feel magical to users while still being maintainable for engineers—tight interfaces, clear ownership boundaries, and systems that scale without becoming fragile.

    I’m based in Ghaziabad, Uttar Pradesh, India, and when I’m not coding, I like stepping out for local street food and a quick evening walk around the city to reset my brain.