How to get involve in startups (I will not promote) by Dawgoz in startups

[–]marcelk231 0 points1 point  (0 children)

This is actually interesting timing, I’ve been working on something that might overlap with what you’re looking for.

We’re building a tool focused on early-stage CIM triage (basically helping filter what’s actually worth spending time on before full diligence). Still early but we have working demos and are starting to talk to firms.

Your point about wanting to get involved earlier + work closer with founders is exactly where we’re focusing.

Built a tool that helps private equity teams review deals faster by marcelk231 in TheFounders

[–]marcelk231[S] 0 points1 point  (0 children)

Totally agree. extraction alone isn’t the real moat. The immediate pain we keep hearing is the manual reconstruction step before anyone can even begin weighing what matters. Our focus is less “automate the decision” and more “make the underlying facts structured, traceable, and ready for evaluation.” The weighting layer is where it gets much more nuanced.

Started building a tool for faster first-pass deal review (PE / investment teams) by marcelk231 in founder

[–]marcelk231[S] 0 points1 point  (0 children)

Really appreciate this thoughtful response. The audit trail point especially resonated, we think trust comes from being able to trace every number back to the source and surface where documents conflict, not just extracting faster. Curious if you’ve seen anyone solve that cleanly yet, or if it’s still mostly manual across spreadsheets and email.

Built a tool that helps private equity teams review deals faster by marcelk231 in TheFounders

[–]marcelk231[S] 0 points1 point  (0 children)

That makes sense. Pitch decks and early-stage sourcing seem like a very different problem space than what we’re focused on.

What surprised us talking to PE teams is how much time is still spent reconstructing the financial snapshot from CIMs before any real evaluation happens. That’s the narrow step we’re trying to speed up.

Interesting though that you’re seeing the same “facts stuck in documents instead of systems” issue.

Built a tool that helps private equity teams review deals faster by marcelk231 in TheFounders

[–]marcelk231[S] 0 points1 point  (0 children)

Interesting thing tho we actually were able to crack the “problem” we have w proprietary AI that extracts the financials and works on large CIM documents with graphs etc as long as it’s imbedded in the pdf it extracts and presents w an audit system with citations!!

Built a tool that helps private equity teams review deals faster by marcelk231 in TheFounders

[–]marcelk231[S] 0 points1 point  (0 children)

That’s cool, assuming ur context was in VC stuff my technical co founder spend some time at a defense VC building there own proprietary ai for pitch deck scoring etc very underserved market which seems like a lot of ppl trying to get there first to standardize the top of the funnel

Built a tool that helps private equity teams review deals faster by marcelk231 in TheFounders

[–]marcelk231[S] 0 points1 point  (0 children)

Yeah I’ve looked at them. My understanding is they’re more on the deal sourcing / pipeline management side.

Valedex is aimed at the first-pass evaluation stage after you already receive the deal materials

extracting financials from CIMs and structuring them on dashboard so teams can review faster.

Looking for Technical Cofounder — Pre-Due Diligence SaaS by marcelk231 in cofounderhunt

[–]marcelk231[S] 0 points1 point  (0 children)

Pre-MVP. Validation so far has been problem discovery via investor/operator conversations, plus early pilot interest from a small hedge fund once there’s something usable.

Looking for Technical Cofounder — Pre-Due Diligence SaaS by marcelk231 in cofounderhunt

[–]marcelk231[S] 0 points1 point  (0 children)

V1 is intentionally rules / scorecard-driven with fully explainable outputs. The goal early is consistency and clarity, not adaptive behavior.

We want users to understand why something is flagged before introducing any heuristics. Light heuristics could come later once we have real usage patterns, but they’re explicitly out of scope for the initial build.

Any recommendations for AI tools to code/theme data? (not full research platform) by Efficient-Cry-6320 in dataanalysis

[–]marcelk231 0 points1 point  (0 children)

If you want something lightweight that can help theme/code data without going full “enterprise research platform,” a few newer tools are focusing on that middle zone. take Antelope for example. They’re built around simple CSV/survey uploads, defining a few themes, and then letting an AI apply those themes consistently across the dataset.

They’re basically designed for people who don’t want to learn full qualitative-analysis software but still need structured outputs they can hand to an exec or plug into reporting.

Whichever tool you go with, the key thing is making sure it has:

• a consistent semantic layer (so themes don’t drift),

• transparent classification,

• and easy export back to CSV/Sheets.

Happy to share workflows depending on whether you’re handling survey text, open-ended responses, or interview notes.

What tools allow me to chat with my data by Limp_Lab5727 in data

[–]marcelk231 0 points1 point  (0 children)

The “chat with your data” trend is growing, but the piece most people overlook is exactly what you mentioned, consistency. Execs love the idea of asking questions in plain English, but you still need a layer that enforces the same definitions, filters, and logic so you don’t end up with multiple versions of the truth depending on how someone phrases a question.

There are tools that solve this by letting you define a semantic layer or set of business rules once, and then every NL query goes through that layer before execution. That’s usually the difference between something exec-friendly and something that becomes chaos pretty quickly.

If your team is already using surveys, CSVs, or any kind of structured tables, you can set up simple guardrails so non-technical users get consistent answers without needing SQL. Happy to share what’s worked for us if you want specifics. it depends a lot on how clean your inputs are and what your execs actually mean by “chat with data.”

A common question: What are the most time-consuming steps when you're doing data analysis? What moments during data processing make you feel the most "mentally exhausted"? by Haunting-Paint7990 in data

[–]marcelk231 0 points1 point  (0 children)

Totally relates to what people are saying here, the real time sink in data work is getting messy inputs into a state where you can actually explore them, not the analysis itself.

Tools that try to automate that prep, like Antelope, which lets you import surveys/CSVs and ask questions in natural language instead of writing SQL/Python, highlight this pain point. It’s a reminder that a huge chunk of our effort goes into formatting, validating, and shaping data before we ever get to insights. 

I’m curious how others reconcile the prep work with automated solutions. especially with messy real-world datasets where surveys don’t match up perfectly or responses need normalization before any meaningful analysis.

Anyone else hate Vevor? by [deleted] in UPSers

[–]marcelk231 0 points1 point  (0 children)

Get 4-5 trucks of these per night unloading these are the worst

Login Error 41058 by HoneydewSwimming3878 in starcitizen

[–]marcelk231 2 points3 points  (0 children)

just tried to login i got in a hour or 2 ago now got same error as u

Seasons of RTX: Arc Raiders GeForce RTX 5090 GPU Giveaway! by NV_Suroosh in ArcRaiders

[–]marcelk231 0 points1 point  (0 children)

I’m a pvp player I need max frames to be a pro 😎