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🗺️ The biggest challenge in commercial real estate valuation isn't finding data—it's separating market noise from true geographic value 📉. For the Land Value Analysis Platform, we built a high-precision GIS spatial model powered by 🤖 AI regression layers to evaluate multi-variable zoning, historical sales, and parcel boundaries instantly 📊. Result? Investors and developers pinpoint high-yield land opportunities 10x faster ⚡
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Landing page for an AI-native terminal platform
Your own secure AI workforce, built on your own data.
Most SMEs pay for one expensive, generalist AI that knows nothing about their business. We're flipping that: a small, focused AI assistant for each department (HR, Accounts, Marketing, Sales, and Operations), each trained on your own business data.
How we build it:
The result is lower cost, higher accuracy, and an AI that actually understands how your business runs.
We're piloting this internally at Indigloo first. If you run an SME and want to see a department assistant in action, DM me. 🚀
For the internal pilot, I'd keep a held-out question set per department and compare RAG alone with RAG plus fine-tuning. Which department do you expect to benefit most from tuning, and what errors would you want it to reduce?
Portfolio note: Shakehand, my AI cold-email platform.
The feature I thought would sell it: AI-personalized sequences. The feature that actually mattered: deliverability. SPF/DKIM/DMARC monitoring, warmup, inbox placement. Nobody cared how smart the emails were until they reliably landed in Primary.
Lesson I keep re-learning: the unglamorous infrastructure IS the product. AI is the demo. Reliability is the sale.
Agree. The best sequence is worth nothing if it lands in Promotions or spam. Gmail and Yahoo made it harder in 2024: bulk senders now need DMARC and one-click unsubscribe. Curious how Shakehand handles a brand new domain: does it cap daily sends during warmup automatically, or leave that to the user?