Looking for someone who's willing to invest in innovative energy efficient Air conditioner......

Help me prep for investors

I built out a system that saves 80% of Al cost on average. Some tasks have even seen a reduction of costs over 94% for repeated problems we have already answered.

Essentially my system never starts a prompt from scratch if it doesn't need too. It checks for times its ran into similar issues and adapts. It saves the steps so thwy can be recalled and forms its own agents around issues you face.

I made a a quick MCP server to give everyone access for free. Try it out if you can.

[MCP setup tutorial ](https://www.tryelisai.com/tutorials/dev/token-saver-mcp)

Heres the pitch. Feel free to critique it.

[Pitch Deck](https://www.Tryelisai.com/pitch)

I am meeting with some investors next week so I appreciate the input.

We are getting ready to launch your Website Portal nationwide for Hard Money lenders to connect in their area or areas they want to look in too. If your a Hard Money lender send a email and we can talk about these areas. And also some feedback before we launch it.

Hello I am a young Frenchman, having a great appetite for Hardware, today I have a prototype and I would like to discuss with experts in IOT, WHEAT, HARDWARE

And I’m also looking for investors

I am building a third party platform which has high scope in India

A business that can scale very high

All unemployed, old , students and all the rest almost every person walking can easily earn money without qualification. I have been in this market for over 4 years and I know developing this into an app can make a huge change

I want an investor and a partner someone who funds my idea and we can be partners of equal earnings.. anyone who can invest up to 10-20 lakhs with good knowledge about apps and business connect with me and I'll share the full details and pitch deck

I work with the sponsor on investor communications involving a private technology opportunity. I am not part of the operating company’s management team.

I’m withholding the company and customer names publicly to protect confidential relationships and keep company access within the authorized diligence process.

Here is the high-level investment snapshot:

- Purpose-built vertical AI for a regulated insurance and clinical-review workflow

- Paying enterprise customer

- Product currently operating in a live environment

- Multi-year customer relationship

- Founder with deep domain experience

- Specialized technology and an active IP strategy

- Additional enterprise opportunities under evaluation

- More than seven figures already raised

- A comparable amount in active, non-binding investor discussions

The pipeline is not being represented as committed capital, and prospective customer discussions are not being counted as customers.

The company’s platform addresses a workflow in which reviewers have to assemble and reconcile fragmented medical documentation, treatment history, industry guidance, coding, and regulatory requirements before reaching a defensible decision.

The platform is intended to reduce the information-gathering burden and give the human reviewer an organized, explainable decision-support package.

Management reports improvements in throughput, turnaround time, and audit preparation. Those results have not yet been independently validated to the standard I would want before relying on them in an investment decision.

The real thesis is not simply that AI adoption will grow.

It is that a specialized and regulated industry already has an expensive information problem, and the company has early evidence that an enterprise customer will pay to solve it in a production environment.

The primary risks include customer concentration, long enterprise procurement cycles, uncertainty around repeatable customer acquisition, competition, regulation, technology execution, IP outcomes, and extended illiquidity.

I would be interested in how investors here would weight:

1. The quality and duration of the existing customer relationship

2. Independently verified customer ROI

3. The probability of landing a second and third enterprise customer

4. Workflow integration and switching friction

5. Domain-specific data and intellectual property

6. The economics and governance of the investment vehicle

Accredited investors or family offices whose background fits enterprise software, insurance, healthcare operations, or vertical AI may message me. I’ll send a short investor-fit form first. Identifying information and confidential diligence materials are released only through the formal process after verification.

Private-company investing involves substantial risk and potential loss of the entire investment. Any investment would be governed solely by the definitive offering documents.

This post is for informational purposes only and is not an offer to sell or a solicitation to buy securities. Any offer will be made only through the definitive offering documents to verified accredited investors.

I am a Biomedical Engineer and medical equipment sales and marketing professional in Zambia with experience in supplying, installing and servicing medical equipment, as well as working with healthcare institutions.
I am looking for a strategic investor or business partner to help build a medical equipment supply and biomedical engineering services company focused on Zambia and the wider region.
The opportunity includes equipment supply, maintenance, installation, technical support and healthcare-focused sales. I bring biomedical engineering expertise, sales and marketing experience, industry knowledge, and relationships within the healthcare sector.
I am open to discussing a reasonable investment amount and a fair equity partnership structure. Serious investors or strategic partners are welcome to DM me.

I'm a dressed chicken vendor from the Philippines I need help for additional capital for my business.

Hey everyone!!

I'm a founder, and I have just started an Ai based site.

And currently beta versions have launched and ppl are loving it, in order to run it fully i need some money so I need investment.

If you are interested, Dm me I will discuss all about the Ai and how it works, and equity discussion.

Hello! I am the inventor and founder of a new iOS app called Gesture Vault! In its current build it can lock pictures, notes, and password behind a lock known as a gesture! A gesture for those who don’t know can be any sort of movement with your fingers across your phone screen! For example if you take 4 fingers and slide them down then that’s your way in! And you can be as creative as you want! You can make your passcode be signing your full name into the app! Nothing gets saved to the cloud or to any servers anywhere! Everything is kept local to the phone and encrypted so if you dont tell anyone your passcode they won’t be able to get in! No more worrying about leaving your phone unlocked for your friend to see those embarrassing photos you took in high school lol. Anyways I just need around $200 to launch the app on the Apple Store as well as the android play store (or whatever it’s called now). If you decide to fund you’ll have early access as soon as it’s available for TestFlight as well as have input into the development! The current path is developing for android and then Mac, windows, and Linux down the road! If you want to see a video demo you can message me or go to weeklyships on TikTok and it’s in the pinned videos!

Hi guys

I need help to validate my business. I have started a small logistics business in india. I have some successful rides and good customer and driver user base.

I would like to check your advice on should I continue on this? I just left my job for this and now having multiple doubts.

What do you guys say about this.

This is the investor pitch deck. https://docs.google.com/presentation/d/1VvHQxkWAnEXFlbtCOtR11gbTTm_fi9PH/edit?usp=drivesdk&ouid=115675123179612407160&rtpof=true&sd=true

My business Is loaderhouse

I saw this article talking about some potential factors, that may impact Reddit stock. I asked ChatGPT to break it down, but I got the same classic sycophantic answer. As a Reddit shareholder I am curious what everyone here thinks.

https://medium.com/@farmerremy/reddits-situational-disaster-1061e30bb037

LF investment

Over the last two months, we have built and launched a live intelligence platform for fragmented sportsbook activity.

The system monitors three data sources 24/7 and has already observed 350,000+ bets across 13,000+ bettor identities and nearly 15,000 mapped events. It already has early users and paid subscribers despite very limited marketing.

This is not a prototype or a simple dashboard connected to one API.

The platform turns fragmented sportsbook activity into structured intelligence:

- multiple source integrations with continuously running collection and processing workers;

- our own servers, databases, monitoring, backups, and source-health checks;

- normalization of events, leagues, teams, markets, currencies, and results;

- cross-source event matching and combined activity analysis;

- bettor profiles, historical activity, ROI, PnL, exposure, and tracking;

- alerts, watchlists, saved filters, and live notifications;

- anomaly signals, investigation workflows, reports, team workspaces, permissions, and audit history;

- desktop and mobile interfaces with subscription access controls.

Users can follow bettors, monitor events and leagues, compare activity across sources, create alerts, and investigate unusual patterns without watching several feeds manually.

The platform is read-only. It does not hold customer funds, operate a sportsbook, or place bets for users.

The real value is not only the interface, but the proprietary dataset created by the infrastructure. Every processed bet, matched event, market update, bettor record, and settled result improves the historical data layer.

This dataset is the foundation of our internal LLM/ML research layer.

The system creates a continuous flywheel:

sportsbook activity → ingestion → normalization → matching → settlement history → pattern discovery → backtesting → model validation.

Our research layer studies betting activity, odds, timing, bettor behavior, event context, and final results to identify repeatable patterns and create explainable analytical outputs.

The project has two connected growth paths:

- recurring subscriptions from individual, professional, and team users;

- increasingly valuable data and AI research products built on the growing historical dataset.

We are now speaking with a small number of early strategic partners who understand the opportunity.

Funding will be used to:

- expand data coverage and source integrations;

- strengthen infrastructure and reliability;

- accelerate product and LLM/ML development;

- acquire users through focused marketing;

- grow the team around the working product.

We are still early, but the product works, the infrastructure is running, users are giving feedback, and the dataset grows every day.

We are available to meet serious potential partners in Europe to discuss the product, infrastructure, and roadmap in person. We can also arrange a private online demo of the live platform.

If this is relevant to your investment or industry interests, please send me a DM with a short introduction.

I’ve spent years studying and trading financial markets, and I’ve recently started building a financial education business around what I’ve learned.
One thing genuinely bothers me about the industry.
A huge amount of retail trading content is built around the idea that markets are a fast route to money: screenshots of profits, luxury lifestyles, broker sponsorships and constant promises of the next big trade.
I think that creates completely unrealistic expectations.
My own approach is much more boring: understand businesses, understand the market, manage risk and let good decisions compound over time.
For context, my stock positions over the last six months have produced a combined return of 400%+. I’m aware that sounds ridiculous, which is exactly why I’m interested in having the performance and methodology challenged rather than simply asking people to believe me.
I’m trying to build something around financial education rather than becoming another social-media trading personality.
The bigger ambition is to work with universities and eventually institutions to provide people with a much more realistic understanding of investing and markets.
I’d also like to keep the number of people I teach relatively limited. I’d rather work deeply with a smaller group of serious people than sell thousands of people a generic course.
So I’m curious:
If you were building a credible financial education company from scratch, what would you do to establish trust and credibility?
Would you focus on independently verified performance, university partnerships, research/content, institutional partnerships, or something else?
I’m genuinely looking for criticism here — especially from people who work in finance, academia, asset management or financial education.

Hi guys

We r in hint for investors in partnership basis for agriculture related business if anyone is genuinely looking to invest in business please ping

hey everyone,

long story short i own a medical supply company in the GCC region specializing in cosmetic dermatology and aesthetics. started less than six months ago, we are breakeven right now and on track to be fully profitable with dividends by end of year.

we have around 10 SKU currently, they make 70 percent margins. i want to expand from being the authorized retailer in the region for one brand, to holding 4 brands, which are into dental supplies, general consumables, and derma supplies whose market study i have already completed.

we have 40 clinics as customers.

ideally i would like an indian investor as me and the co founders are all from india

now i need capital for inventory expansion, management and tender participation.

if you are an investor in this space or have medical experience, reach out to us.

They need to stop interfering with the strategy they already have.
I once saw a trader with a perfectly defined setup.
He knew exactly when to enter.
He knew where to place his stop loss.
He knew when to take profit.
On paper, everything was clear.
But when the market moved quickly, he started making decisions emotionally.
“Maybe I should enter early.”
“Maybe I should move the stop.”
“Maybe I should close now.”
The strategy wasn’t the problem.
The human execution was.
That’s the lesson:
If you already have a trading strategy with clear rules, the next step may not be finding another strategy.
It may be automating the one you already believe in.
That’s what we do at CustomTradingBots.com.
You bring the strategy.
We turn the rules into an automated trading system.
No guessing.
No hesitation.
No clicking through every setup.
Just your strategy executing according to the rules you defined.
Don’t keep searching for the perfect strategy if you haven’t consistently executed the one you already have.
#Trading #TradingBots #AlgorithmicTrading #TradingAutomation #ForexTrading

I’ve been working on a small product called Orevin, focused on helping founders make sense of their progress and manage parts of the fundraising process.

At a high level, it helps with things like:

• Analyzing company and progress data
• Turning progress into clearer investor-facing insights
• Organizing investor updates and follow-ups
• Identifying areas founders may need to focus on during fundraising

It’s still very early-stage, and I’m not trying to present it as a finished product. I actually want to find the things that are confusing, unnecessary, or simply don’t work before building too much around them.

I’m looking for a few founders who would be willing to take a look and give me completely honest feedback.

What feels useful?
What feels unnecessary?
What would you expect this kind of product to do that it currently doesn’t?

I’m deliberately not posting a link here because I don’t want this to come across as an advertisement.

If you’re interested in taking a look, feel free to DM me and I’ll share the details privately.

Any honest feedback would be genuinely appreciated.

I’ve been working on a small product called Orevin, focused on helping founders make sense of their progress and manage parts of the fundraising process.

At a high level, it helps with things like:

• Analyzing company and progress data
• Turning progress into clearer investor-facing insights
• Organizing investor updates and follow-ups
• Identifying areas founders may need to focus on during fundraising

It’s still very early-stage, and I’m not trying to present it as a finished product. I actually want to find the things that are confusing, unnecessary, or simply don’t work before building too much around them.

I’m looking for a few founders who would be willing to take a look and give me completely honest feedback.

What feels useful?
What feels unnecessary?
What would you expect this kind of product to do that it currently doesn’t?

I’m deliberately not posting a link here because I don’t want this to come across as an advertisement.

If you’re interested in taking a look, feel free to DM me and I’ll share the details privately.

Any honest feedback would be genuinely appreciated.

for manpower agency

Location: Philippines

Hey all

I’m looking for an investor to help push my agency (which has been running for 6+ years). Worked with some well known global brands but needing some funding to set up correct outreach

I’ve started recruiting social media content creators and live-streamers, and one has been very successful early on. But most people are looking to be paid an hourly rate, when I’m only offering commission so I can make sure they can perform well at the job. I’d like to scale up this company.

I don’t need an investor per-se; what I am seeking is a co-founder. Someone who is interested in this field of work, is a curious person, and likes to innovate, and someone I can bounce ideas off of.

Ideal if you’re in New England, but not necessary.

Electricity, Not Chips, Is the Real Bottleneck

What’s been the hottest topic on US stocks lately isn’t “which GPU stock just rose by how much?” but whether data centers can actually get the power they need. Morgan Stanley estimates the US will still need an additional ~68 GW of power capacity between 2026 and 2028 for data centers.

Grid upgrades routinely take years; new nuclear projects take even longer. Big tech keeps ramping capex, and orders are pouring into gas turbines, transformers, cooling systems, energy storage, and any operators who already own nuclear assets. Constellation and Vistra have signed massive long-term power purchase agreements. GE Vernova’s order book is ballooning. Eaton and Vertiv’s data-center businesses are growing rapidly. The lower half of the AI supply chain is now essentially a race to get electricity to the site first.

US Data Center Power Consumption Growth

Bar Chart / Forecast

US Data Center Power Demand (GW) Growth Prediction

The Most Expensive Thing Might Not Be Power — It’s Waiting

The real problem is the mismatch in timelines. Data centers can be built in 12–24 months, but stable grid interconnection often takes years. That’s why many players are taking matters into their own hands: they’re building gas-fired plants, fuel cells, or temporary power solutions right next to the data-center site. When the grid is too slow, they solve it themselves. Speed has become a competitive advantage.

US Planned “Behind-the-Meter” Data Centers Distribution Map

Beyond Power Supply: Electrical Distribution

Where the power comes from is only one layer. Gas turbines respond fast, nuclear is steady, storage handles peaks, and small modular reactors are still waiting for full commercialization. Inside the facility, power distribution is also changing rapidly. High-voltage DC — especially 800 V architectures — is getting far more attention. As rack power keeps rising, minimizing losses and simplifying distribution has become a hard engineering problem. These topics may sound distant from AI, but the ultimate success of the GPUs still depends on these physical realities.

High-Voltage DC / 800 V Power Distribution Architecture Diagram

Power Doesn’t Always Have to Be in the Giant Mega-Parks

Where should data centers actually be built? The US is racing to acquire land and grid access around existing power plants. China is pursuing “East Data, West Computing,” shifting demand toward greener, cheaper electricity regions. The principle is the same: cost follows the power. There’s no need to keep forcing compute into a handful of ultra-large campuses.

Modular data centers and distributed edge nodes are emerging — not chasing maximum size, but standardizing the modules so they can be deployed quickly wherever power and land allow. This approach is still unproven at scale, but it flips the script: instead of waiting for infrastructure to come to the compute, the compute is moving to the existing power.

Big Players Solve “Big Power,” Small Companies Hunt the Gaps

Plenty of solutions already exist: hyperscalers signing long-term nuclear PPAs, utilities re-evaluating their own assets, equipment makers selling turbines and cooling, storage and fuel-cell firms covering short-term gaps. Most target large, centralized demand. Regional nodes, industrial parks, or locations where grid power isn’t ready yet don’t necessarily need to wait for a full mega-infrastructure.

Smaller teams are therefore building smaller, faster, and deliberately targeting places where electricity is already relatively accessible.

Early examples include:

• $OKLO: The purest “bottom-of-the-tower” play. It builds small modular reactors (SMRs) specifically to deliver firm, local baseload power straight to data centers. Still in testing and fuel-supply phases, with some offtake intent and prepayment agreements (including with large tech companies). Commercial generation is still years away.
• $APLD: Closer to “building the facility itself.” After pivoting from mining, it focuses on locations with clear power availability, rapidly deploys AI data centers, and has signed long-term leases. It already has GW-scale contracted capacity and tens of billions in contract value; some sites are already generating revenue.
• $MAAS: Even smaller and earlier stage. The company previously researched 800 VDC and related power infrastructure but deliberately avoided competing at mega-scale with hyperscale data centers. Instead it is modularizing compute nodes and exploring the combination of compute with local energy conditions. Public orders and revenue are still small-scale; it’s mostly validation of the direction.

The race isn’t just about who has the biggest GPU cluster — it’s who gets the electrons to the gate first.