Ho Bae

Founder working on the messy data problems behind enterprise AI. PhD background in AI/privacy. Building tools for AI agents, sensitive data, and data readiness. Sharing what we learn along the way.

Products

LLM Capsule
Redaction turns a row into "*** signed with *** on ***, ***", then "*** escalated payment terms on ***". You can't tell if that's one person or two. Capsule gives the model "[PERSON_A] (Sales) signed with [ORG_1] on [DATE_1], [AMOUNT_1]" and "[PERSON_A] escalated payment terms on [DATE_2]". Names are gone both times. What's left is who's who and what sat where, enough for the model to work with, and your real values come back inside your environment. Sensitive isn't just PII. Deal terms, internal metrics, code names. What's still manual on your team because of what's in the data?
Syntitan
Your agent answered one way in March and another way in June. Code unchanged, model pinned. So you go looking at the data, and the table has moved on. Nothing left to compare against. Syntitan binds every run to the data state it read: run 0412 to release 8f2a, run 0619 to release c71d, and diff 8f2a c71d tells you which three columns moved and which one the agent actually reads. It doesn't stop data from changing. It turns "what did this run see" from an investigation into a lookup. How do you answer that question today?

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Recent activity

Building an AI product taught me that the LLM isn’t the hardest part

Built a tool that catches when AI agents quietly get worse — looking for 2-3 people to try it free

I built an open-source PII masking layer for LLM APIs — early traction, looking for design partners

I got banned marketing my own products on Reddit, so I built a tool. 19 months later: 400 paying founders, $56K, zero ads

Can making data “cleaner” actually make an AI agent worse?

Built 2 SaaS and got 0 customers. Here's how.

What started breaking when your team grew from 40 to 70 people?

Why I stopped relying on pure LLM APIs (and started pre-building my AI's "brain")

I spent 3 months debugging why an AI voice agent kept booking appointments in the wrong timezone (and what it taught me about shipping AI pr

Can making data “cleaner” actually make an AI agent worse?

Co-founders suck…

Can making data “cleaner” actually make an AI agent worse?

Solving privacy wasn't enough — why no one used our AI tool (and what we fixed)

The AI Paradox: Everyone wants the productivity. No one trusts where the data goes.

The AI Paradox: Everyone wants the productivity. No one trusts where the data goes.

Most SaaS products fail for the same boring reason

Stop Spamming Reddit for MRR. It’s Killing Your Brand (You need Claude Code for BuildInPublic instead)

I Thought AI Made Me Faster. My Metrics Disagreed.

I killed my "commodity SaaS" to build an AI Growth Team. Here’s why.

I launched 2 apps on Product Hunt and both were featured — here's what I learned