GenXAI Analytics IPO
GenXAI Analytics IPO AI Bet Entering the SME Market: The GenXAI Analytics IPO is an NSE SME book-built issue worth ₹54.84 crore, entirely a fresh issue of 0.47 crore shares, basically the company’s way of saying “we’re here to scale, not sell old baggage”, you get the idea. At its core, GenXAI Analytics works in the AI and enterprise tech space, building tools for enterprise planning, decision-making and generative AI solutions, somehow it all feels like the same direction just different labels. In plain terms, it’s trying to turn messy business decisions into something a bit more “smart system, less guesswork.” Picture it like companies get an AI co-pilot that doesn’t take coffee breaks, or at least it won’t. With AI demand booming, the IPO is clearly trying to ride the hype wave, but whether it lands as a smooth flight or a bumpy ride will depend on execution not just algorithms, because reality has its own rhythm.
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GenXAI Analytics IPO Timeline |
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|---|---|
| IPO Open Date | June 5, 2026 |
| IPO Close Date | June 9, 2026 (5:00 PM UPI mandate deadline) |
| Allotment Date | June 10, 2026 |
| Refunds / Demat Credit | June 11, 2026 |
| Tentative Listing Date | June 12, 2026 (NSE SME) |
| Category | Details |
|---|---|
| Price Band | ₹110 – ₹116 per share |
| Face Value | ₹10 per share |
| Retail Lot Size | 1,200 shares (₹1,39,200 minimum investment) |
| Retail Maximum | 2 lots / 2,400 shares (≈ ₹2,78,400) |
| HNI Minimum | 3 lots / 3,600 shares (≈ ₹4,17,600) |
| Employee Discount | ₹10 per share |
GenXAI Analytics isn’t just raising ₹54.84 crore “for fun”, there is a real kind of plan behind it, you know. First, part of that money will be pushed into working capital, basically keeping the day-to-day engine ticking along so the whole operation scales up without drama. After that, there is debt repayment, because every growing company eventually wants to tidy up its balance sheet and get a bit more breathing room. And then, there’s a chunk that’s kept aside for product development as well as capital expenditure, so it can fund new AI tools, upgrade the tech stack, and strengthen the platforms. In a simple way, stabilize the finances , keep the operations fueled and build smarter AI products for the next growth jump.
(This information is for educational purposes only, not financial advice. Investors should verify details independently before making decisions.)
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