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Day Zero retweeted
you bet :)
we help you get the best inference there is -- at the best price possible
DM me or reach out at cal.com/team/routerplus/plat… to talk with our team
Founders: Are you on text with your business customers?
Met with a startup founder who had just been texting his largest customer (which informed him over text that they were rolling out the product more broadly).
Texting with your best accounts is a sign of strong, trusted relationships. In fact, if you're NOT texting, it means that the relationship is not strong enough.
Get on text!
Day Zero retweeted
Replying to @Dzerovc @origin_autonomy
With us from Day Zero, literally! Thank you 🙌
It gives you a different Hit, seeing something on a white board to real life & that's what it feels right now, as @origin_autonomy emerges out from stealth!
The trio has built bots that are live in NY
& have delivered 100K sq ft finished walls.
Glad to back them on their Day0.
Thrilled to announce that @origin_autonomy has raised $20M in total funding, co-led by @Accel and @ZacuaVentures.
Excited to be building this with @ashishxdaga, @tusharmakkar08 and the super talented team at @origin_autonomy. We’re building general-purpose robots for interior construction.
Special thanks to @johnkoetsier at @Forbes for covering our journey.
News Article: tinyurl.com/ym2vj7ts
Day Zero retweeted
It's not been too long @yogesh_origin & I were white boarding on a problem to go behind, from there to here, all in a few months 🚀
Today @origin_autonomy emerges form stealth, with bots that paints walls on its own at 3x human speed.
Insanely luck to have backed them @Dzerovc
Thrilled to announce that @origin_autonomy has raised $20M in total funding, co-led by @Accel and @ZacuaVentures.
Excited to be building this with @ashishxdaga, @tusharmakkar08 and the super talented team at @origin_autonomy. We’re building general-purpose robots for interior construction.
Special thanks to @johnkoetsier at @Forbes for covering our journey.
News Article: tinyurl.com/ym2vj7ts
Day Zero retweeted
today @useRouterPlus was top of the @ycombinator digest that goes out to all YC founders and alumnis 🥳
Day Zero retweeted
ScaleDown's Constrained Decoding Models (CDMs) are now available on @useRouterPlus. You can now use their Classify, Summarize, and Extract models which feature a 1M input token context window, multimodal (text + image) today at:
app.routerplus.com/?modality…
You already gave the LLM the answer. So why is it writing it out from scratch?
Introducing a new AI model architecture: Constrained Decoding Models (CDMs)
LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable.
CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive.
Not just a decision model, but a family of 3 CDMs live today:
• Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection.
• Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction.
• Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests.
Built for production:
• 1M tokens of multimodal (text + image) input, 31x larger than Jev
• 77.2% on DecisionBench vs Jev's 72%
• 200x faster, 467x cheaper than frontier LLM APIs
• $0.05/M input tokens. Output is free (yes, even for summarize)
Live on your favorite platforms today:
@OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus
Get 50M input tokens for free (for the first 50 hours) at link below 👀
Day Zero retweeted
Getting your inference right shouldn't be hard.
@useRouterPlus (YC F26) is live: the right model and provider for your workload, at the best price.
check out : routerplus.com/capacity
Day Zero retweeted
ok so we’re growing faster than I can keep up. I’m now the bottleneck.
Hiring semi-technical generalists for growth and founder’s office roles. Full-time and interns. Start ASAP.
SF preferred. Remote works if you learn fast.
DMs open. tell me the craziest hack you’ve pulled off.
What an insane way to see what truly performs! 🙌🏽
Replying to @alokbishoyi97
Here's a fun benchmark we ran: 8 decision models playing Tetris. In our tests @perplexity_ai Decider came consistently at the top !! ( cc @AravSrinivas )
you can try em out here - app.routerplus.com/playgroun…
Day Zero retweeted
Launching Decision models on @useRouterPlus. You can now use various system 1 decision models such as Jev, @perplexity_ai Decider, @bespokelabsai Nimble, Mercury Decide, Clef, Kev 4B and Decider 2B with 3 models free !!
app.routerplus.com/playgroun…
Day Zero retweeted
btw at @useRouterPlus we have been using numerous techniques to ensure that inference providers are ACTUALLY delivering what they claim - this involves running relatively expensive live evals , checking quality and also measuring symmetric KL divergence to monitor deviations from actual expected behaviour
since a lot of inference contracts go through us we can actively monitor for such discrepencies and hold providers accountable. its only done now for certain larger contracts - but we expect to roll it out to the wider platform soon
Yesterday I posted about inference price war pushing margin down. But I since learned inference scammers are a thing with shady price manipulations:
As inference providers,
- You can lower your input token price 100x cheaper but up your output price 5x. You rank higher in openrouter in price but tots cost is much higher.
- You can quantize the model to serve cheaply but users are buying a shittier model.
- You can retain and sell user data elsewhere to make more money.
- You can secretly swap to DeepSeek v4 flash but say it’s GLM 5.3 10% of the time.
Therefore it’s hard to know
1. You get the model you ask for
2. You pay for the tokens you actually burn across cache input, input, output and
3. Your data is safe.
I’m sure openrouter is working on it AND baseten, fireworks, together and other enterprise brands will continue to thrive even with higher pricing because they sell peace of mind.
Day Zero retweeted
Buying inference today means picking between two bad options.
Commit for a year and pay for capacity you don't use. Or go serverless and get rate limited the moment you grow.
But usage arrives in bursts: a weekend eval, a two-week backfill, US business hours.
And not all tokens are equal. You might need BF16, not quietly quantized FP8. Served in the US. A latency target. Zero retention. Fast tokens for your product, cheap batched tokens for the rest.
The capacity exists. It's just scattered across big clouds and long-tail providers you've never heard of.
So we built a marketplace.
Introducing the @useRouterPlus managed inference marketplace.
Post the inference you need, when you need them. Commitment you are comfortable with. Providers bid. You pick the one that meets your spec.
we're already on track for 1 trillion tokens a month.
routerplus.com/capacity
Day Zero retweeted
Life update: moved to SF and started YC F26.
It’s been a whirlwind , but being around so many sharp, ambitious founders has already pushed us to move much faster.
@EVO__HQ is starting to click too.
We help companies figure out the right AI for their products , which models to use, how to run them, and where to get the best combination of quality, reliability and cost.
We’ve already been working with larger AI teams on real production workloads, and YC has accelerated a lot of those conversations. We will soon start posting more on our progress
If your company is spending seriously on AI inference, experimenting with open-source models, or wondering whether your current setup is actually the right one, reach out !!
Day Zero retweeted
Our thesis is that this will accelerate over the years.
We see a more new age founders building for the globe than before!
Indian founders have built 205 unicorns abroad, creating $560 billion in value: Prosus
Founders who grew up in India have built 205 unicorns outside the country, with these companies accounting for around $560 billion in founder-share-attributed company value, according to the Indian Diaspora Index by Prosus and Dealroom.
The index tracks overseas unicorns with at least one founder who grew up in India. The companies include Zscaler, Rubrik, Nutanix, Skild and Palo Alto Networks.
moneycontrol.com/news/busine…
Day Zero retweeted
Congratulations @RohanNayak2 and the entire @PocketFMTeam on this massive milestone, reaching $500M ARR, doubling it in just a year, and doing it while staying EBITDA profitable.
The post is well worth the 1,300 words, especially the part about how they reinvented themselves, killed what wasn’t working, and stayed focused on the customer journey and great storytelling.
Nothing is obvious on day zero. It’s the constant grind of learning, iterating, and getting better that eventually shines through.
Proud to have played a small part in this journey when @miten, @soaibgrewal, and I wrote their first check at @TimesInternet, alongside @kumarharsha2212 and @LightspeedIndia.
We grew from ~0 to $500M ARR, adding $250M last year alone while being EBITDA profitable.
1,300-word post on every growth tactic that worked for us:
1. What got us from 0-$400M ARR in the US works in every country.
2. Retention and Monetisation Hacks.
3. Localization > Translation.
4. Experiment with $1M internal seed checks.
5. Pivoting to only AI content production unlocked 100% ARR growth.
Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios.
1. Acquisition Playbook for 0-$10M ARR in any country in 6 months
We run a 90 sec video trailer of an audio drama as an Ad and ask users to download the app if they're interested in the rest of the story.
Our core insight after spending >$100M on acquisition is: If the clickthrough rate (CTR) for an ad goes from 2% to 2.25%, our customer acquisition cost (CAC) decreases by ~ 30%.
We remodelled our system around this insight and built an AI-first 2.25% CTR ad manufacturing machine that works in every country.
For every new country, we take our hit shows -> use LLMs to extract and most intriguing moments -> Write a 5-min script combining all the best parts. The first 60 seconds has to have a hook every 5 seconds and needs to end with a crazy cliffhanger to force a download mid-scroll.
If a marketing video is not hitting our benchmarks (2.5% CTR and 55% 3-second through-play), a creative director gets involved to change the hook or cliffhanger to get the numbers there.
AI lets us make 1,000 Ads per show, and in total we do ~17.5k Ads per month. When a business creating scales from 1k to 10k Ads, the normal thing is for CAC to skyrocket. But with what I just shared, we 7-8x'd our User Acquisition budget without increasing our CAC materially.
It took us 8 months to figure this out, but then the timeline from 0-$10M in every country got shorter and shorter:
US revenue grew to $25M in 19 months. (US is now 78% of total)
Germany to 21M in 11 months.
France to $10M in 3 months.
2. Retention and Monetisation Hacks.
We knew we wanted to create an audio entertainment platform, but there was no standard format. For the first 2-3 years, we tried 10 different formats before landing on the winner.
After we got it right with audio drama (8-12min chapters, written for mobile fiction, serialized, episodes have strong hooks and end on cliffhangers), avg daily streaming time went from ~25mins to 150+.
Audio drama made us realize that Pocket FM was creating a whole new medium. There was no playbook for anything that we were doing. Everything had to be thought & built from scratch.
This is what we did for each major bullet:
- Monetization: Users have some free daily minutes to listen; then it's pay per episode. We also added the option for users to unlock episodes by watching ads, which is doing extremely well. Ads scaled from zero to a ~$90M run rate in 12 months.
- Engagement & production: You don't become obsessed with an app you open once a week. To have users engage daily, we make the next episode free every day. Also helps them build the habit.
- Discovery. Huge problem because people consuming Pocket FM enter the app, tap the show, and lock the screen. We fixed it by doing "playlists" of episodes. Once users's free minutes on a show are done, we ask users if they want to pay. If they say no, we play a new show, one where they haven't used their free mins. And we stitch episodes of different shows together that way, creating natural discovery.
3. Localization > translation.
78% of our revenue is still concentrated in the US. Localisation is fixing this: You might write a show for a Spanish audience where language, jokes, folklore, have a certain flavor; if you merely translate the show for, say, a Norwegian audience, that color is lost and hurts the show in the Norway. Listeners would relate more if the show was written by a Norwegian.
That's why, instead of translating, we localize shows to different regions. We use AI to take the spine of stories and adapt their whole cultural layer to the other country.
The results: a US show that was localized for a German audience had 50% higher retention than the translated version.
Localization + our user acquisition playbook led to:
- $10M+ ARR in France within 3 months
- $21M+ ARR in Germany within 11 months.
And this expands writers' addressable market.
We get messages of writers thrilled to have revenue coming from the US, India, EU, LatAm, without them doing much incremental work.
4. Experiment.
We give $1M checks to new internal initiatives, and the team has 12-18 months to prove their thesis. If they prove it, we double down.
This is how Pocket Saga came about, our AI video microdrama app. It's an AI video equivalent of Pocket FM. Same shows and structure, but as a vertical 2-min mobile video series.
We launched it two months ago and it's at ~$15M ARR.
Pocket's broader thesis is to help creators tell their stories to as many people as possible. Start with audio drama -> multiple languages or localize to diff countries -> microdrama -> more formats like movies, TV shows, and games.
Best of all is that writers get revenue streams not only from countries they wouldn't have tapped into, but also from formats they wouldn't have thought possible.
5. Pivoting to only AI content production unlocked 100% ARR growth.
In mid-2024, we pivoted to only AI content production.
Our growth took a very direct hit. Pocket was already at $200M ARR, growing 50% YoY, and we flatlined for a whole semester.
Six months later, the business exploded.
After the switch, we went from ~25k hours of content produced per year to over 2.5M hours, which are also higher quality. Because AI orchestrates the writing and more data is fed into it, more blockbusters come out.
Over 90 titles have $1M+ in lifetime earnings and 13 crossed $10M.
Quality control is done with LLM as a judge, and LLMs are quite tough.
Results are very encouraging:
- 12-month revenue retention went from 44% to 76%.
- In the past year, we added $250M in net new ARR.
__________________________________
Pocket Entertainment (Pocket FM + Pocket Saga) has become the largest AI entertainment platform.
We have the largest storytelling catalog with 770,000 titles, 550k creators, and 5.5B hours of playtime with minute by minute retention & engagement data. We are using all of this data to improve every aspect of our business.
Our Bet: In the next 3 years we will be able to produce Naruto-like series for $1000.
Netflix has to spend $17B to find 100 Blockbusters per year.
What happens when you can produce 1M high quality shows for $1B?
The streaming wars caused a $300B reallocation of market cap.
The AI entertainment wars may be a $1T+ reshuffling of market cap.
We are at a unique spot. Unlike other AI creator tools like Runway or Midjourney, we own both the supply and demand side of AI content.
We've attracted over 550,000 writers who are producing an annualized 2.5M hours of content every year. This pairs with 137B+ minutes streamed.
Because of this, growth is accelerating as we scale further.
We have multiple S-curves inflecting at the same time:
- AI produces better and more ads -> scale faster in new countries
- Writers + AI produce more shows -> more blockbusters
- Localisation -> more reach per blockbuster
- Audio to video format expansion -> larger TAM -> more creators
Every aspect of our business is designed to improve another, and everything is aligned so that the number of blockbusters continues to rise.
If you're interested in building at the intersection of ai, tech and entertainment, DM me.
Go Rohan 🚀🚀
In mid-2024, Pocket FM was at $200M ARR, growing 50% YoY, and we decided to kill its business model.
Revenue flatlined for six months, we turned cash flow negative, and investors were writing us off.
But then, Pocket's ecosystem exploded.
Our reasoning and why this happened:
What constrains Netflix's growth is content. They spend $17B+ on content production yearly, but many shows don't make it to the final stage. Of those that do, only a few become blockbusters. And those few are the reason subscribers stay on Netflix.
So we started thinking. Pocket was growing nicely. However, what limited us was how many new users we could add and retain at scale. The only solution we came up with was increasing the number of blockbusters. Blockbusters drive user growth and retention at the same time.
To get more blockbusters, Pocket FM needed more production.
That's why we pivoted to only AI Content production.
This did a number of things:
1. More content gets produced because we removed a lot of friction from doing so. It's easier for writers to maintain daily production. And for writers who still haven't found their hit show, testing and pivoting becomes less time-consuming. From taking several months to test even one show, you can now test 3-4 shows in one month.
2. Content quality increases. The more content gets produced and consumed on Pocket, the better the engine gets. We continuously monitor retention and other engagement metrics. When we detect something is working, our writing copilot learns it.
3. Unlocked hundreds of thousands of writers; Pocket's writing copilot is built to help writers without storytelling training.
This is in contrast to Netflix's model. While their budget gets allocated among a limited number of studios, Pocket's supply side is getting flooded with writers. Over 500k writers are producing on our platform.
4. Made it easier to cross-create ads to attract users. Better shows are easier to sell to people who aren't yet using Pocket. And the same data that feeds our copilot goes on to feed the engine we use to create ad videos, which is also self-reinforcing.
_____________________________
After making the change, ARR flatlined for six months and we started losing money. It was extremely painful, but then growth and the whole ecosystem exploded.
- Hours of content produced per year went from 35k to ~2.5M.
- New titles added yearly more than tripled from 120k to 400k+
- Millions of new users joined Pocket.
The obvious risk was opening the gates to AI slop. That's why we have an extremely rigorous feedback and moderation process
Ultimately, the only thing that matters is whether users are enjoying the content that's being uploaded. Metrics don't lie:
- 12-month revenue retention went from 44% to 76%.
- Avg daily streaming time went from ~25mins to 150+ mins.
- DAUs/WAUs from 30% to 51%.
I think we're extremely early, and I'm excited to see how Pocket's flywheels continue to accelerate from here.
Day Zero retweeted
Great thesis on @evo__hq / $EVO.
~ @ycombinator Fall 2026 adds another strong validation layer to 25K+ installs, 1.4K GitHub stars and >1B tokens/day already served pre-YC.
~ @alokbishoyi97 also brings serious pedigree: ex-@dzerovc and early personal investor in @neondatabase before its ~$1B Databricks acquisition.
Real traction + strong builder + YC. The dots keep connecting.
~ CA: 0x721b072dbb616f29eea73ac004e03fd4e884bba3
~ DYOR / NFA.
~ @0xDeployer @igoryuzo @Dannyhbrown
Getting into Y Combinator opens up several major advantages for Evo and is extremely difficult—acceptance is rare, not common.
Immediate funding ( 500,000 in every accepted company as soon as they are accepted (not when the batch starts) $375,000 on an uncapped SAFE with Most Favored Nation terms
This gives Evo runway without needing to raise a separate seed round right away.
@evo__hq just got into @ycombinator Fall 2026.
Founder @alokbishoyi97 background is cleaner than most people realize:
• Ex capital allocator at @Dzerovc ($`200M fund)
→ Full-cycle early-stage investor (sourcing, diligence, LP work, portfolio support)
→ Personally worked ~12 companies → 6 raised Series A,
2 reached Series B 🏌♀️
• Made a personal angel check into @neondatabase (serverless Postgres)
→ Neon later acquired by @databricks for $1B (2025)
→ Pure personal investment.
He’s now full-time building $EVO — an autoresearch + intelligent routing layer that continuously hill-climbs AI inference workloads (the single largest cost center in AI).
Already (pre-YC):
• 25k+ installs
• 1.4k GitHub stars
• Serving >1B tokens/day
• Users seeing 30–60% lower inference costs
• Router hitting Pareto frontier on agent benchmarks at ~20× lower cost than frontier models
YC capital + network + Demo Day on top of real technical traction + a founder who has both invested capital and generated a strong personal outcome = high signal.
The program is one of the most selective startup accelerators in the world. Recent data puts the acceptance rate at roughly 0.6–2% per batch (often trending below 1%), depending on application volume.
batchstack.org
0x721B072dbb616F29eEA73ac004e03Fd4E884bba3
Applications: Typically 15,000–25,000+ (sometimes 20,000–40,000+) per batch. YC itself has referenced over 10,000 applications every three months.
roundfunded.com
Companies accepted: Usually 150–250 per batch (recent figures often ~150–200 after YC switched to four batches per year). Examples include ~196 for Winter 2026 and lower numbers (around 140–170) in some 2025 cohorts.
wearefounders.uk






















