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rahul ✓

@rahulgs · NYC · joined 17 Dec 2014

@tryramp CTO

17 166Followers
1 281Following
715Posts total
6.2MViews on collected posts

Latest posts

https://t.co/j5uOZVIy8c 17.1K views · 226 likes · 5 reposts · 11 replies Open on X →
@rahulgs Cool 2.6K views · 21 likes · 1 reposts · 0 replies Open on X →
@rahulgs Excited to support invoicing at Ramp! 3.9K views · 48 likes · 2 reposts · 1 replies Open on X →
@rahulgs https://t.co/jUhm2GxJtH 1K views · 18 likes · 0 reposts · 0 replies Open on X →
Grok 4.5 is #1 at processing real-world invoices At Ramp, we tested models on 150k bills submitted by actual businesses, scoring them on whether they predicted every correction a human would make Grok achieved the highest perfect-extraction rate, beating similarly priced models 4.4M views · 1.2K likes · 98 reposts · 120 replies Open on X →
@rahulgs Ramp to $100B+ 345 views · 6 likes · 0 reposts · 0 replies Open on X →
@rahulgs The next AI infrastructure layer isn’t about adding more models. It’s about sending each request to the right one. 4.3K views · 19 likes · 6 reposts · 0 replies Open on X →
@rahulgs Great idea. Congrats on the launch 1.6K views · 5 likes · 0 reposts · 0 replies Open on X →
Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue Across 100+ use cases in our product, keeping all up to date with the right model is a challenge - Either we're losing out on intelligence for the dollars we spend, or we're https:/
0:12
961.3K views · 1K likes · 71 reposts · 106 replies Open on X →
now there's nothing stopping you from trying: grok make me a $1 billion dollar b2b saas make one mistake 17.6K views · 85 likes · 0 reposts · 6 replies Open on X →
Every company used to start with paperwork. The next generation will start with a prompt. Ramp for Agents lets AI agents incorporate your company, apply for Ramp, and get your business ready to spend, pay bills, and manage money. https://t.co/OgjpSDNxyq 158.4K views · 297 likes · 21 reposts · 24 replies Open on X →
In many ways, finetuning or RLing a custom model is a bet against model progress and scaling. It's to choose to say "we don't think there's going to be a good enough base model for this task anytime soon, so we're not going to wait" with oss release velocity these days, its a 179.6K views · 1.1K likes · 53 reposts · 30 replies Open on X →
https://t.co/v1tcKZ2PHF 430.4K views · 602 likes · 56 reposts · 20 replies Open on X →

Against accounts of the same size

1 posts from the last 90 days, next to the 10K–100K follower range. shown to more people than peers of the same size.

Median views17 126this account924median for 10K–100K
Reach, %99.77%this account3.62%median for 10K–100K
Engagement, %1.41%this account1.52%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post17 12692418.5×
Reach (views ÷ followers)99.77%3.62%27.6×
Engagement rate1.41%1.52%0.93×

Others in this range →   Compare with another account →   How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

430.4K1 Jul
179.6K
158.4K7 Jul
17.6K
961.3K20 Jul
1.6K
4.3K
345
4.4M24 Jul
1K
3.9K
2.6K
17.1K19 Aug

Last 13 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.16%1 Jul
0.66%
0.23%7 Jul
0.52%
0.14%20 Jul
0.31%
0.58%
1.74%
0.03%24 Jul
1.73%
1.30%
0.84%
1.41%19 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes64.7%4 652 in total
Reposts4.4%313 in total
Replies4.4%318 in total
Quotes3.5%250 in total
Bookmarks23.0%1 656 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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