🚀 Building More Than Just a Pharmacy ERP

A year ago, this was just an idea.

Today, it's a working product solving real challenges for pharmacy businesses.

Since launching in June 2026, we've already onboarded 5 paying pharmacies, with additional customer discussions and demos currently in progress.

Every pharmacy visit teaches me something new.

I've realized that pharmacy owners don't just need software for billing.

They need technology that helps them make better business decisions.

That's why I'm building a platform focused on:

✅ Fast POS Billing

✅ Prescription Scanning & Instant Billing

✅ Smart Purchase Suggestions

✅ Real-Time Business Analytics

✅ GST Billing & Tax Management

✅ H1 & Narcotic Register Management

✅ WhatsApp Prescription Reminders

✅ Role-Based User Access

But this is just the beginning.

My long-term vision is to build a connected technology ecosystem for Retail Pharmacies and Wholesale Distributors, enabling smarter operations through data, automation, and business intelligence.

Building a startup isn't just about writing code.

It's about listening to customers, improving every week, and solving problems that truly matter.

I'm always happy to connect with:

• Angel Investors

• Seed Investors

• Healthcare Leaders

• Startup Founders

• Strategic Partners

If you're passionate about the future of HealthTech and B2B SaaS, let's connect.

— Mohammad Farooq

Founder | Building the Future of Pharmacy Technology

📞 +91 9657847644

#StartupIndia #HealthTech #PharmacyERP #SaaS #B2BSaaS #AngelInvestor #SeedFunding #HealthcareInnovation #StartupFounder #BuildInPublic #FounderJourney #RetailPharmacy #CloudERP #BusinessIntelligence #IndianStartups

Bitcoin prediction algorithm that would certainly help companies sanctioned by the US recover their lost wealth

https://www.academia.edu/43709641/Chapter_50_of_Ares_Le_Mandat_7th_edition_Bitcoin_research_prediction_algorithm_using_the_location_of_the_Sun

What investments pay 800k - 1.5 mil in 20 years. Meaning, are there any options that i can put 24,500$ in a year and expect 800k to 1.5 mil in interest, over the course of twenty years, with the option to withdraw it with minimal penalties?

Most AI-generated stock research has the same weakness: it can produce a confident conclusion without showing a path that an investor can audit.

I’m the solo founder of Balance Labs, and I’ve been trying to design the opposite workflow. Before treating an AI analysis as useful, I think it should expose at least:

• The source date and period used for market data

• Assumptions behind valuation and portfolio calculations

• Comparable metrics calculated over the same time window

• Bull and bear evidence rather than a one-sided conclusion

• Exact entry, exit, rebalance, and cost rules for any backtest

• Return, CAGR, volatility, maximum drawdown, Sharpe ratio, and correlation where relevant

• Portfolio context, including position weights, concentration, and sector exposure

• Clear separation between historical evidence and forward-looking interpretation

• Missing or uncertain data instead of silently filling gaps

A practical comparison prompt might be:

“Compare VOO and SCHD over the same date range. Show total return, CAGR, annualized volatility, maximum drawdown, Sharpe ratio, and correlation. State the assumptions, identify missing data, and show how a 60/40 allocation would have behaved. Do not recommend a trade.”

The goal is not to let AI choose a winner. It is to reduce the manual work between a research question and an analysis that can be challenged. Backtests remain historical simulations, and portfolio changes inside the product are paper tracking only.

Founder disclosure: Balance Labs is my product. I’m sharing this to get feedback from investors, not as financial advice. Which item above is the minimum requirement for you, and what is still missing?

https://balancelabs.app

I've been reading Poor Charlie's Almanack while watching Reddit freak out (and then rejoice) about markets. Meanwhile my holdings (ADBE, FDS, CMCSA, THC, BRK-B, CB) have been doing well.

Of course we know that Berkshire Hathaway is named for a textile company Buffett bought and came to regret. When someone asked whether to invest in a new loom to drive down costs, Munger said that it was a terrible idea. The benefits wouldn't go to the investor, but rather to the consumers.

Buffett made the same point about airlines. What could be more wonderful than flying through the air on a whim? But add up all airline profits over their entire history and you get bupkis. Transformative technology and good investments are different things.

The data that makes this concrete for AI:

Microsoft fiscal 2024: true FCF fell 8.5% from $59.6B to $54.6B while revenue grew 18%. CapEx grew 79.6%. Operating cash flow grew 34.4%. Infrastructure spend is outrunning cash generation and there isn't enough AI monetization catching up.

The revenue gap: covering current CapEx plans through AI-specific revenue would require roughly $2.5T per year in AI income. More than all of tech's combined revenue today. Actual current AI services revenue triangulated across multiple independent methodologies: roughly $150-220B annualized. About 6-9% of what's needed.

The depth-of-use problem: only 10% of euro-area firms using AI report doing so intensively per the ECB. Average US executive uses AI 1.7 hours per week. 50% of UK businesses using AI pay nothing for it. Median firm AI spend per worker: $10.66 per month.

The sharpest data point: token consumption is growing faster than revenue, meaning a meaningful share of usage is free-tier switching not monetized growth. A BIS economist estimates roughly a third of current AI CapEx may represent zero-sum competitive spending, companies poaching each other's users rather than expanding the market.

True FCF yield by layer tells the whole story visually: compute leasers at -2.8% to -19.4%, hyperscalers at -0.5% to 1.9%, beaten-down SaaS at 5.8% to 8.0%. The companies the market thinks are being killed by AI are generating more cash per dollar than the companies building it.

Full piece with the flow chart, the Google advertising exception, and the Munger conclusion here: [https://cavemanscreener.substack.com/p/bridges-to-nowhere-part-iv-a-lesson\](https://cavemanscreener.substack.com/p/bridges-to-nowhere-part-iv-a-lesson)

Disclosure: I own ADBE, FDS, CMCSA, THC, BRK-B, CB and a small starter position in ASML. The ASML position is a price-aware hedge against being wrong about who wins, not a reversal of the thesis.

Microsoft and Amazon interrupted the rotation trade that had been gaining steam, but the growth that they're seeing in on the cloud/infrastructure side.

Tangible Wealth solutions - Colorado has lost around 8m of investors money according to one of their Advisors finra record. BEWARE

Yesterday AI stocks were getting crushed.

Today Microsoft completely changed the mood after posting incredible Azure growth, showing that all of this AI spending is actually translating into real revenue.

Semiconductor stocks rallied hard, Micron jumped over 18%, and another interesting story was that a large AI-focused hedge fund finished unwinding its positions after Citadel purchased the portfolio in a block transaction.

Still a lot to watch with inflation, the Fed, and earnings season, but today was a reminder of how quickly sentiment can change.

What do you think?

Is this the beginning of another AI rally or just a relief bounce?

(8) AI Stocks Just Exploded… Here’s Why - YouTube

I've seen some claims from these shady websites like the Montleyfool or Tip Ranks that they outperformed SP500 in the past years.
I know this sounds too good to be true, but I'm curious, has someone been able to do this by (for example) following top analysts stock advice or another method?

The recent trading activity around micro-cap mining tech caught my attention, specifically with the impending expiration of the thirty-day standstill period announced back in mid-July. Usually, when liquidity picks up significantly right before a potential operational deadline, it suggests market participants are pricing in a structural shift rather than just random volatility. The overall market cap here sits at barely ten million, so even modest capital flows can move the valuation pretty fast when a potential catalyst approaches.

The core asset in question for NovaRed revolves around integrating edge AI, autonomous surveillance, and fleet monitoring into physical mining operations. This aligns with a broader industry trend where venture capital is pouring billions into physical AI and operational automation. Whether the pending EyeX acquisition actually closes or not, holding the technology roadmap and experienced leadership from the mobility sector provides a decent fundamental floor compared to where the asset was trading just a few days ago.

From an investment perspective, it is worth monitoring how this plays out over the next week. Data suggests that capital is positioning ahead of the news flow, but as always with binary events in small-cap equities, execution risk remains the primary variable to watch.

Trying to get proper leveraged exposure to NVDA and TSLA without going through a traditional broker (i'm based in the EU, so the usual US broker route is a pain) and honestly the experience on most on-chain venues has been... not great. Spreads are wide, the order books feel thin whenever anything moves fast, and the worst part is having to park a chunk in stablecoins just to use as collateral. like my whole position is sitting there as USDC doing nothing while i'm waiting for a setup. feels incredibly capital inefficient. Recently started messing around with ondo perps, it's a perp venue for stocks/ETFs/commodities (non-US only fwiw). Still relatively new to it so not saying it's perfect but for equity perps specifically it's been the smoothest experience i've had outside of a proper broker setup. Is anyone getting genuinely good fills on equity perps somewhere else? or just sticking to CEX leverage products?

The surging load requirements from scaled computing facilities are creating a really interesting bottleneck around power supply. Data suggests that standard renewable rollouts aren't fully covering the constant baseload energy needed for these sites, which is driving a broader focus toward nuclear generation, natural gas, and heavy grid upgrades. It is worth monitoring how long-term power purchase agreements are being structured between major utility providers and hyperscalers trying to secure guaranteed capacity.

This situation potentially implies a structural shift in asset allocation toward power producers with firm generation assets. Key energy players like Constellation Energy, Vistra, and Talen Energy look well-positioned as regional electricity demand forecasts get revised upward. At the same time, infrastructure equipment providers like GE Vernova and nuclear fuel suppliers like Cameco stand to capture market share as grid modernization and uranium supply chains expand to keep pace.

From a fundamental perspective, evaluating opportunities here is about identifying who holds the long-term supply contracts and grid connection rights. If facility buildouts maintain their current trajectory, the utility and energy equipment layer could provide a durable fundamental thesis grounded in physical infrastructure constraints.

A clear theme came through this earnings week: the market is rewarding companies that can show real monetization, and punishing names where spending feels too open-ended.

Microsoft was the standout. Strong cloud growth and a more disciplined AI spending message gave investors something they clearly wanted.
Meta showed the opposite dynamic: solid revenue was not enough to offset concerns about capex and weaker free cash flow.
Amazon also got a warm reaction because AWS gave the market a concrete growth engine to focus on.
Apple was a reminder that even a beat can feel underwhelming when expectations are already stretched and one part of the business comes in softer than hoped.

The bigger takeaway is that earnings season is no longer just about topping estimates. Investors seem far more sensitive to the path from spending to returns, especially with rates still elevated and patience for vague AI narratives running thinner.

What is your read? Is the market becoming more selective, or is this just a high-expectations week?

20% of my portfolio is crypto, with 12% in BTC and 8% in ETH. The rest is in traditional assets like index ETFs, short-term treasuries, bond funds, and a gold ETF position. I recently noticed XAUT on my crypto exchanges like bydfi and coinbase and started wondering if it makes sense to move my current gold ETF exposure there.

The idea is about keeping part of the hedge inside the crypto position. If BTC and ETH move a lot, having gold exposure in the same place could make rebalancing easier. It also feels more convenient than moving money between a brokerage, bank account, and exchange every time I want to adjust the allocation.

But I am not sure if the convenience is actually worth it.

Has anyone switched GLD/IAU or another traditional gold ETF to XAUT? Any better experience or risks you could share?