For founders & solopreneurs

Build a market research library you actually use

Save competitor pages, pricing ideas, customer complaints, launch examples, and product positioning the moment you find them. Gleanit keeps the note, source, tags, and context attached, so when it's time to write, position, price, launch, or prompt AI, your market evidence is ready to use.

See how it works ↓

You saw the market clue. But can you find it?

A competitor headline that explained the category better than yours. A pricing page that made the offer feel obvious. A Reddit complaint that named the pain better than your landing page. A launch post that showed exactly how people talk about the problem.

Three weeks later, you're making a positioning decision, writing a landing page, or planning a launch. You know you saved something useful. It is technically somewhere in your tabs, screenshots, docs, bookmarks, or memory.

But now you need the source, the note, the angle, the context, and the examples around it.

So you dig through old links, random screenshots, and half-written docs… then make the decision from scratch anyway.

Capture → Find → Use

From browser tabs to better decisions

The same three moments happen every time you research your market: you capture something useful, try to find it later, and use it when making a positioning, pricing, product, or launch decision. Gleanit keeps that loop connected.

The old way

Sound familiar?

You see a competitor headline, pricing page, launch post, or customer complaint worth remembering.
You screenshot it, bookmark it, paste it into a doc, or leave the tab open "for later."
It gets saved somewhere named Screenshot 2026-03-14 at 11.42.png.
Weeks later, you need it for positioning, pricing, a landing page, investor notes, or a launch plan.
You can't find the source, the note, or why it mattered in the first place.
The useful context is scattered across tabs, docs, bookmarks, screenshots, and memory.
Then you ask AI for help, but first you have to rebuild the research packet from scratch.

With Gleanit

It's actually easy.

Capture market evidence as you browse
Find the source and context later
Use it for positioning, pricing, launch, and AI

See what stays attached

Save the exact competitor claim, pricing detail, customer quote, or page section you noticed
Add the note while the insight is still fresh
Keep the source URL and page title attached automatically
Tag by competitor, pain point, feature, pricing, launch, market, or positioning
Keep each capture inside the right product, idea, launch, or research project
Reopen the original source in one click
Search by keyword, tag, source, or meaning
Compare patterns across competitors, reviews, pages, and saved notes
Invite collaborators to add context to the same research
Keep the evidence behind your decisions instead of relying on memory

For AI workflows

Connect Cursor, Claude, or ChatGPT through MCP
Let AI search the same project-scoped research library you use
Give AI the capture, note, source, tags, project brief, and context in one place
Ask AI to turn saved research into positioning angles, landing page copy, launch ideas, pricing notes, or competitor summaries
Stop copy-pasting screenshots, links, files, and explanations into chat

Oh, almost forgot...

Gleanit also helps you see patterns across the market evidence you save.

So when you are deciding how to position, price, build, or launch, you are not starting from a blank doc. You are starting from the market you already captured.

Actual workflow

Saved many. Made a few. Shipped the best.

Good decisions come from evidence and intuition. Gleanit helps you capture the market as you browse, compare the patterns, and use what matters when it is time to choose.

Captured competitor reviews → found a potential edge

Captured competitor reviews

founder-market-research g2.com

You can get quick AI-generated ad creatives, but only around 30% are actually usable. The results are very inconsistent.

research # competitor # positioning # reviews

founder-market-research g2.com

The concept is great, in theory you can build a full suite of creative assets using the platform.

research # competitor # positioning # reviews

founder-market-research g2.com

The only feature I wish it had was the ability to duplicate whole swipe files with other users.

research # competitor # positioning # reviews

founder-market-research g2.com

Helps centralize all the creative workflows in there for ease and simplicity.

research # competitor # positioning # reviews

founder-market-research More

The rest is a researched secret 😉

research # competitor # positioning # reviews

4+ captured

Found a potential edge

The workflow seems more valuable than the output. People like the idea of AI creatives, but they don't trust the results enough to rely on them.

# reviews # gap

If the output is inconsistent, the real product might be the research/context before generation, not generation itself.

# positioning

Foreplay review is interesting: "centralize creative workflows" is the actual desire. It's not just saving ads. It's organizing the work around them.

# competitor # workflow

The duplicate swipe-file complaint is useful. People want to reuse structures, not just individual saved items.

# competitor # customer-pain

Maybe Gleanit should not compete as "AI creative generation." It should compete as the research layer before decisions, briefs, positioning, and prompts.

# positioning saved for positioning doc

5 notes

Saved competitor reviews revealed a possible edge.

Captured ads / landing pages / customer language → generated campaign angles

Captured market examples

Note foreplay.co

Foreplay: Shows how workflow tools position around saving, tracking, and briefs.