r/angelinvestors

Hi all,

I’ve been building a platform that started as a cybersecurity investigation tool. But as time passed and the core was closer to being complete, I started thinking it might be useful outside of cybersecurity.

The long-term vision is still specific to cybersecurity. But the trust and evidence layer could apply to any team that needs to run a documented investigation, collect evidence, track review steps, keep a clear history, and give an accused or responding party a controlled way to participate.

Here is what it’s built around now:

·        creating investigations and cases

·        collecting and tracking evidence

·        verifying uploaded files instead of just trusting user-submitted claims

·        keeping custody and history records

·        managing review and disposition steps

·        inviting a responding party into a restricted portal

·        letting that person view released materials and submit their own evidence

·        keeping access scoped and auditable

I did some research and I think this might also fit HR investigations, school conduct cases, trust and safety appeals, compliance reviews, fraud and claims reviews, or corporate security incidents. Maybe more.

Right now, the V1 workflow is built, tests are passing, runtime/reproducibility checks are in place, production Helm safety checks exist, edge controls are implemented, restore-drill evidence is documented, and I completed a non-prod rollback rehearsal with a 74-second recovery.

I know that is a far cry from being production ready, so my next step is a tiny private alpha with 2–4 invited people using demo data only.

I have never launched a pilot so I would appreciate some advice on what steps to take (or avoid) or anything else for that matter.

Thanks for the attention.

I spent 10+ years as a financial advisor managing ~$100M, and one gap kept coming up over and over:

People don’t know if they’re actually on track for retirement.

Not balances. Not returns.

Just a simple answer to: am I doing this right?

There’s no clear standard for that today.

So I built one.

What we’re building

EbbScore — a Retirement Score (300–850)

Think of it as a simple way to measure how someone is doing financially for retirement, in one number.

Users:

- Get a free score

- See hidden fees in dollar terms

- Understand what’s helping or hurting them

- Get a prioritized action plan

We don’t manage money and don’t sell financial products.

We’re positioned as an independent layer focused on transparency.

Traction (early but real)

- Live product with full scoring + report flow

- Users can upload statements or connect accounts

- Early traction driven by content + Reddit (multi-million view reach across posts)

- Strong engagement around fee transparency and “am I on track”

Why this could work

The score itself isn’t the main value. The data layer is.

We’re building a dataset of:

- Retirement plans

- Fund fees

- Allocations

- User-level outcomes

Each new user improves the model and expands the dataset.

If this works, it becomes a standardized way to measure retirement readiness across individuals and plans.

Business model

B2C:

- Free score

- $7.99/month monitoring

- Paid reports

B2B (early):

- Employer plan scoring

- Fiduciary risk / compliance positioning

- This also leads to mass adoption on B2C side

Future:

- Benchmarking and data insights layer

- Platform opportunities

Raise

Raising a $250k–$500k equity round via SAFE to:

- Improve scoring accuracy and dataset depth

- Expand distribution (content + partnerships)

- Build monitoring and engagement features

- Develop employer side product

Focused on bringing on partners who understand long-term data-driven platforms.

Why me

- 10+ years in financial services

- Managed ~$100M in client assets

- Built from firsthand experience with how opaque retirement systems are

What I’m trying to validate

- Does this become habit forming or a one time check?

- Is the data moat real and defensible?

- Can this become a standard layer in retirement decision-making?

Ask

Looking for:

- Feedback (especially on moat and distribution)

- Investors interested in early-stage fintech/data platforms

- Critical perspectives — where does this break?

I’ll respond to everything publicly.

Hi everyone,

I’m currently building a platform called Ratelys, focused on helping people make better career decisions by comparing companies in a more structured way.

The idea came from how fragmented company information is today. Salary data, interview experiences, and general sentiment all exist, but they are scattered and difficult to compare meaningfully. Ratelys brings these together and adds structured, community-driven rankings so users can evaluate companies side by side.

So far, the platform has reached around 300 to 500 active users contributing and exploring the data. Early engagement has been encouraging, but retention is still something I am actively working to improve.

I was recently laid off, which has allowed me to focus on building this full time. At the same time, I am currently covering infrastructure and maintenance costs myself, so I am starting to think more seriously about sustainability and growth.

I am looking to connect with people who:

- have experience scaling early-stage products or marketplaces

- are interested in the career / hiring space

- open to angel investment or small sponsorship support (with special thanks/feature on the website)

Happy to share more details, metrics, or walk through the product if there is interest.

Website:

https://ratelys.com/

Appreciate any feedback or thoughts as well. Thanks for reading.

If you’ve played Fantasy Premier League, you already know the pain: by Gameweek 3, half your mini-league has the same three forwards, the same keeper, and the same captain. There’s no skill in that — it’s just luck.

So me and a few mates decided to actually do something about it.

Our platform is a draft-based fantasy football platform we spent a full year building from the ground up. No VC backing, no big team — just a group of football-obsessed developers who were fed up with the same old FPL experience and gave up evenings, weekends, and probably way too many late nights to build something better.

A year of work. A year of iterations. A year of playtesting with our own leagues, fixing bugs at midnight, and obsessing over every detail — because we genuinely believed the Premier League audience deserved a proper draft experience.

Here’s the core idea: Instead of picking freely from the full player pool, every team in your league drafts their squad — meaning once a player is taken, he’s gone. No two teams are ever the same. Every decision matters. Every trade counts.

What we built over that year:

•	Two draft formats — Auction (bid with a budget) and Snake (strategic pick order), both proven formats from American fantasy sports, now built properly for football

•	Head-to-head competition — you play a direct fixture each gameweek, not just a points leaderboard

•	Super League support — scales up to large groups, not just 8–10 mates

•	Real money mini-games — Score Predictors and Last Man Standing run alongside your league for cash prizes

•	Custom team & league branding — logos, identity, the full experience

•	Transfers, waivers, lineups — full in-season management just like the pros

What’s coming next — AI Integration

This is where it gets really exciting. After a year of building the foundation, we’re now planning AI-powered features that will take the platform to the next level:

•	AI Draft Assistant — real-time recommendations during your draft based on your league’s pick history and player form

•	Personalised Transfer Suggestions — AI that analyses your squad weaknesses and recommends the best waiver/transfer targets each gameweek

•	Opponent Scouting Reports — AI-generated previews of your head-to-head opponent before each fixture

•	Predictive Scoring Models — machine learning models trained on historical Premier League data to forecast player points

•	Smart Notifications — AI alerts for injuries, fixture difficulty changes, and price rises before deadlines

Why this is a multi-million dollar opportunity?

Let’s talk numbers. The global fantasy sports market is valued at $8B+ and growing rapidly, yet draft-format football in the UK is almost entirely untapped. Platforms like Sleeper and ESPN Fantasy have proven the draft model works — Sleeper alone reached a $325M valuation purely on the back of NFL draft fantasy. There is no equivalent built natively for the Premier League, the most watched football league on the planet with 3.2 billion fans globally.

The Premier League already has 11 million+ FPL players — a ready-made audience that is frustrated with the same stale format year after year. Capturing even 1% of that audience with a subscription or entry-fee model puts this firmly in multi-million dollar territory. Add real-money competitions, AI premium features, and potential expansion to the Champions League, La Liga, and beyond — and the ceiling here is enormous.

This isn’t a passion project anymore. It’s a scalable, monetisable sports-tech platform sitting on top of one of the biggest untapped gaps in the fantasy sports industry.

We built that platform. From scratch. Because we wanted it to exist.

We’re a small passionate team, the product is live after a year in the making, and we’re now looking to speak with investors who understand the sports-tech and AI space. If you believe in founder-led products built out of genuine passion and real graft — and you can see the same massive opportunity we do — we’d love to chat.

DM open, or drop a comment below 👇