AI Chat

An AI chat that actually knows what you know.

Chat inside Summify with any source you've saved — or with an entire pod. Every answer is grounded in your actual content, with citations back to the original. No setup. Works on web and mobile.

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Copywriting Experts
Eugene Schwartz · Breakthrough Advertising
Stefan Georgi · RMBC framework
Alex Hormozi · $100M Offers
Joe Sugarman · Seminar notes
I'm writing a new sales page for our Pro tier. Which framework should I use?
Three frameworks in the pod fit a SaaS sales page: Schwartz's market sophistication levels to pick your headline angle, Georgi's RMBC (Research → Mechanism → Belief → Close) as the long-form spine, and Hormozi's value-equation stack for the offer section. Start with Schwartz to choose your awareness level, then build on RMBC.
Schwartz · ch.4
Georgi · 12:08
Hormozi · 18:42
Generic AI #1
vague · generic
Generic AI #2
vague · generic
Generic AI #3
vague · generic
Same question. Same vague answer. Every time.

Generic AI chat doesn’t know about your stuff.

You open Claude or ChatGPT. You ask about the framework your team uses. The deck a founder sent last week. The exact thing your customer said in interview #7. The answer comes back generic — the average of the internet, written by no one you trust. You can paste the source in. But you’ve already done that twice today. And tomorrow you’ll do it again. And on your phone, the context is gone. And the conversation history is buried in a sidebar you’ll never find again.

One chat. Every source. Grounded answers.

Open the source in Summify and start asking. Open the pod and ask a question that spans every video, podcast, and document in it. Every answer quotes the exact passage with a timestamp or page back to the original. Your conversation history is saved next to the source it came from, so you can pick up the thread weeks later.

Chat · 18 customer interviews
What did everyone say about onboarding friction?
Three patterns across the pod: first-run setup felt heavy (Interview 3, 11, 14), unclear pricing during signup (Interview 5, 7, 12), and no clear next step after install (Interview 2, 9, 17).
Int 3 · 09:18
Int 5 · 22:11
Int 9 · 14:02
Int 14 · 31:46

How it works

Lex Fridman × Demis Hassabis
Ready to chat
Transcribed
Structured
Indexed
1

Drop a source or open a pod

Add a YouTube video, podcast, PDF, article, or voice note. Or open an existing pod with a stack of sources already inside. Summify has already transcribed, structured, and indexed everything — chat is ready the moment processing finishes.

Summarise the methodology.
Pull out every quote about pricing.
Compare the two approaches discussed.
What did they actually say about onboarding?
Ask anything about this pod…
2

Ask anything

"Summarise the methodology." "What were the three counter-arguments?" "Pull out every quote about pricing." "Compare the two approaches." Ask follow-ups. Switch sources mid-conversation. Ask across the whole pod.

Three sources address this directly: the Lex × Demis interview frames it as a research-first problem; the YC playbook reframes it as a distribution problem; the GTC keynote treats it as a compute problem.
Lex × Demis · 1:42:18
YC Playbook · p.34
GTC 2026 · 47:02
3

Get answers, grounded and cited

The AI quotes the exact passage from the actual source, with a timestamp for video/audio or a page for documents. Click the citation to jump to that point in the source. Your full conversation history is saved automatically.

Why Summify

Grounded in your content

Quotes the exact passage from your source. No hallucinations. No averaging the internet.

Cited every time

Every answer links back to the timestamp or page in the original. Click to jump.

Multi-source pod queries

Ask a question that spans every source in a pod. Get one answer drawn from all of them.

Works on every source type

YouTube, podcasts, PDFs, articles, voice notes — all chattable, all citable.

Conversation history that sticks

Every chat is saved against the source or pod. Pick up weeks later.

Built-in, no setup

No keys, no config, no external tool. Open Summify and ask.

Web and mobile

Same chat on your laptop, your phone, your tablet.

130+ languages

Ask in any language. Get answered in the same.

Stop pasting context into chat windows.

Free trial. Full access. Cancel anytime.

Summary
Chat
Why does the author think that?
Because in Chapter 4, they argue that…
What's the counter-argument?

The difference between summary and conversation.

A summary tells you what the source said. A conversation lets you interrogate it. You can ask why the speaker thinks what they think, what evidence supports it, what counter-arguments came up, what you’d push back on if you were in the room. Summify chat turns every saved source into something you can think with, not just something you’ve read.

Customer Research · 18 interviews
Interview 1
Interview 2
Interview 3
Interview 4
Interview 5
“What did everyone say about onboarding?”
Across 18 interviews, the consistent theme was first-run friction — cited in 11 of them.
Int 3Int 5Int 9Int 11Int 14

Multi-source pods change what you can ask.

A pod of 20 customer interviews lets you ask "what did everyone say about onboarding?" and get one answer drawn from all 20. A pod of 50 research papers lets you ask "what’s the consensus on protocol X?" without re-reading any of them. A pod of your own past work lets you ask "what have I already said about this?" before you write the next thing.

Lex × Demis Hassabis
Conversation history · 12
Today
What did Demis say about scaling laws?
3 days ago
Summarise the section on AGI timelines
Last week
Pull out the bits about AlphaFold
2 weeks ago
What does he think about open-source models?

Chat history that survives the week.

Most AI chats vanish into a sidebar you’ll never open again. Summify saves every conversation against the source or pod it came from. Open the source three weeks later and the chat history is right there — every question you asked, every answer, every citation. Especially useful for ongoing research, client work, and deep deals.

Podcast2h 41m
How frontier AI labs actually train models
Dario Amodei × Lex Fridman
Ask this deep-dive anything
What does Dario say about RLHF?
Dario calls RLHF a “veneer” — useful for shaping output, but not a real safety solution on its own. He argues constitutional AI plus interpretability research are the longer-term bets.
42:18
1:08:44

The same engine that powers Discover.

Every deep-dive in the Summify Discover library uses the same chat engine you’ll use on your own pods. So before you sign up, you can already test it — open any deep-dive and ask it anything. If the answers feel good there, they’ll feel the same on your own knowledge.

Frequently Asked Questions

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