Pre-Seed

EdTech, AI / ML, B2C

How Litero AI Raised an $800K Pre-Seed in 5 Months From 8 Investors

An AI writing platform for students. A solo founder raised an $800K pre-seed from eight investors in five months, almost entirely through warm intros.

Raise snapshot

Raised

$800K

Duration

5 months

Investors

8

Check size

$50k–200k

Valuation

$5M post SAFE

Revenue at close

$300k ARR

The investor funnel

Investors reached25
First meetings2080%
Second+ meetings1352%
Term sheets832%
Investors reached25
First meetings2080%
Second+ meetings1352%
Term sheets832%

Raise materials

Pitch deck (PDF)

The company

  • AI writing platform for students, focused on academic research papers

  • Raised $800K pre-seed in 5 months from 8 investors — 5 VCs, 3 angels

Founders

  • Alexey Pokatilo, solo founder

  • Ex-BCG

  • Previously co-founded an EdTech company that grew past 200 full-time employees

Pipeline and channel

  • Sourced entirely through personal network — warm introductions from friends working at VC funds

  • Reached investors — 25

  • First meetings — 20 (80%)

  • Second+ meetings — 13 (52%)

  • Term sheets signed — 8 (32%)

  • Lead investor came from a chance meeting unrelated to fundraising

Timeline and runway

  • Fundraising start — February

  • Talks and due diligence — April

  • Term sheets received — May

  • Money in the bank — June

  • Runway at start — 7 months

  • Already had revenue, so runway worked as a dial, not a countdown

Pitch deck and data room

  • Data room — pitch deck, P&L with historicals and projections, cohorts, legal documents

  • Legal documents — incorporation docs and team contracts

  • Data room was assembled during due diligence, not before it — investors said what they wanted to see

Most common rejections

  • Regulatory doubt: whether universities would allow or ban AI writing tools

  • Defensibility: fear that ChatGPT or Claude would replace the product

  • Business model: many investors don’t invest in B2C, or hold it to a much higher bar

Metrics at close

  • Revenue at close — $300k ARR

  • Valuation — $5M post-money SAFE cap

  • Check size range — $50k–200k

  • Angel checks near the $50k floor; most VC checks came in higher

Lessons learned

  • Cold outreach works — cold connections turn warm quickly

  • Prepare the data room before you start

  • Would be more proactive with warm and cold outreach next time

  • Would expand the number of investors in the round and increase round size for a healthier runway

  • Avoid agreeing to unusual terms early — default to a simple SAFE

“Don’t underestimate cold outreach — I’m surprised how quickly cold connections turn warm.”

— Alexey Pokatilo, founder of Litero AI

Full interview

00:24 — Let’s talk first about the funnel you’ve had. How many investors did you reach out to?

Alexey — We talked to about 20 investors in total. And, as you said, we ended up with a pre-seed round with eight investors joining — five VCs and three angels.

00:47 — You reached 20 investors. How many first meetings did you have?

Alexey — Practically, we had first meetings with everyone. It’s worth saying that those 20 to 25 outreach messages were all warm introductions — either from the investors that were about to join the round, or from friends and acquaintances. So there was a pre-qualification: we had a first meeting with everyone, and a good proportion of those resulted in second meetings as well.

01:08 — How many of them conducted a second-plus meeting? Half of them, or more?

Alexey — I think a bit more than half, to be honest.

01:26 — What was the check size range that you received?

Alexey — We raised with a minimum $50,000 check size. The angels were at $50K, and some of the VCs were at 50 as well, but most were higher.

01:49 — How did you build this pipeline? You said you used just warm introductions — did you use any other sources?

Alexey — I didn’t know you guys before then, so I didn’t have the luxury of a very streamlined outreach. I honestly went to those of my friends who work in VCs and asked them to make relevant intros to the VCs and angels they believed might be a good fit for us. That was the main source of leads.

Alexey — And our lead investor was actually a random meeting — we got introduced not even in the context of raising money, and that sparked the whole fundraise, to be honest.

02:40 — When did you start your fundraising, and how long did it take in total?

Alexey — The whole conversations and gathering everyone took about three, three and a half months, and then there was due diligence — say a month or a month and a half — where we already had commits. At early stages the benefit of doing due diligence early is that there isn’t a lot to check, so it runs much faster than when you already have traction and a bigger team.

Alexey — So it was one and a half months of due diligence or so, and then very quick wiring. We were super lucky to have very responsive investors — all of them were quick and prompt.

03:19 — What was your runway when you started your fundraising?

Alexey — It was about seven months or so. But the important nuance is that we already had revenue at the time, so the runway for us was more of a dial, not a countdown. We could have extended it by playing with how quickly we grow, by cutting costs, and things like that. So it was not that big of a pressuring factor, I’d say.

03:58 — What was your revenue when you started your fundraising?

Alexey — Around $300,000 ARR.

04:22 — Did you have any valuation cap on your SAFE?

Alexey — Yes, we had a $5 million cap.

Anna — Post-money cap?

Alexey — Post-money cap.

04:41 — What did you include in your data room — pitch deck, P&L, cohorts, legal documents, anything else?

Alexey — It was my first fundraising exercise in my career. I sort of went into due diligence without a data room and ended up, at the end of due diligence, with a data room, so to speak. We were educated by our investors on what they want to see there, and we stored it there.

Alexey — So: the deck. We did have an actual P&L with all the history of transactions since we launched. Cohorts were an important part — relatively simple, because at early stages of the product you don’t have a lot of different dimensions; we didn’t have a lot of different countries or types of users, so it was pretty straightforward. And then a lot of legal documents about company incorporation, and contracts with our team that we had to re-sign properly. A pretty standard set of things.

06:00 — What were the most common reasons investors said no to you?

Alexey — We’re a platform that helps students write their research papers and do their research, so we’re focused on the academic market. One of the biggest challenges for investors was whether universities would allow products like that, or try banning them, or try regulating them.

Alexey — To me it was obvious, from my background in EdTech, that it would be impossible to restrict AI use in universities, and that they would just be slightly slower in adapting to it — but they would have to adapt. Mind that this round started a year and a half ago, so back then it was a legitimate question where the market would go. Now it’s safe to say universities are starting to adapt to AI usage; some of the things they ask students to do require students to use AI.

Alexey — Another concern, still very much relevant back then, was how you’re going to defend against ChatGPT and Claude Cowork expanding. I think that’s the main concern for most AI companies now — LLM wrappers, be it thin or thick wrappers. That was hard to address.

Alexey — We always had a product in mind. Interestingly enough, Claude Cowork did not exist back then, and the vision of the product we had was pretty much aligned with what Claude Cowork shaped up to be. So now we have to think next step, next step, next step.

Alexey — And the third rejection reason — more of a concern — was that some investors don’t work with B2C, or don’t like working with B2C companies outright. That was probably the most numerous one. Even now, for our current fundraising round, the single biggest source of rejections is that we just don’t look at B2C, or if we do, it has to be something exceptional and something we truly believe in. So the bar is even higher.

08:31 — What are your top fundraising tips for founders?

Alexey — Don’t underestimate the importance of cold outreach. Everyone says that, but I’m surprised how warm things can turn, and how quickly, from cold outreach.

Alexey — Second: have the data room prepared before you start. It’s super easy — they’re all pretty standard. It just makes things so much quicker and doesn’t slow you down.

09:16 — If you had to raise this pre-seed round from scratch again, what would you do differently?

Alexey — I think I would be a bit more proactive with warm and cold outreach. I would try to expand the number of investors within the round right away, and I would probably increase the size of the round a little bit — not dramatically. It’s important not to underestimate how much money you might need to have a healthy runway.

10:00 — What’s one fundraising mistake founders should avoid at all costs?

Alexey — I think going for, or agreeing to, weird terms at early stages. It’s super important to default to very simple instruments such as a SAFE — or, even if it’s an equity fundraise, something very simple without a lot of terms.

10:23 — When do you plan to start your next fundraising?

Alexey — We’re in fundraising mode right now. Summer in EdTech is usually a slower season, which is normally unexpected, but we already started our fundraising and we’re hoping to speed it up as we go into the autumn season.

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