Pennylane
Buying intent
24 tracked signals | Top 15 topics are below | Sales and Marketing are carrying most of it.
Attention by team
LinkedIn activity, by teamWhere Pennylane's own people are actually spending their attention, by team, by topic. Bands run Low to High against the busiest pairing on this page, and each cell also shows how much of that team's own activity it represents.
Topics being researched
30-day windowEvery tracked topic, ranked by volume, not by our guess at what matters. Confidence is the classifier's own certainty that a signal belongs where we've filed it.
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We track the full taxonomy across every account in the graph — including themes not shown on this page.
Who's active at Pennylane
verified title on fileTitles, seniority and topic straight from each person's own activity, with a LinkedIn link so you can check any of them yourself.
See everyone, not just the first 10
12 people across every department at Pennylane, plus a LinkedIn profile link for each.
Primary products / business lines
LinkedIn company profilePennylane is building the financial OS (Operating System) for European SMEs. A single source of truth for financial and accounting data, used on one side by entrepreneurs to run their business (invoicing and getting paid, paying suppliers and expense management, piloting cash and profitability) and on the other side by their accountant for bookkeeping and tax filings. Saving time to all entreprene
Top accounts researching Pennylane
names withheld on the public pageThese are companies whose own people brought up Pennylane unprompted, not accounts we guessed might be interested. We can't yet tell an implementation partner from a genuine buyer here, names unlock along with the buyer profile below.
129,094 companies · 649,540 people are researching Artificial Intelligence
Pennylane's own team shows 8 signals on this topic. No one outside Pennylane has been seen researching the company by name yet — so this is the market it sits in, not a list of its buyers.
- Account Executive3,295 cos · 9,748 people
- Use Case5,473 cos · 13,448 people
Buyer profile
company size · seniorityCompany size and how senior the people involved are, the two things that decide whether this is a real deal. Competitor overlap isn't computed yet for this account.
Buying committee functions
Employee job titles (LinkedIn)Sales — 3 people; HR / Talent — 2 people; Marketing — 1 person; Engineering — 1 person; Finance — 1 person
What's been said
public posts by Pennylane's teamNo public post naming Pennylane has surfaced in the past year, so this is what Pennylane's own team is posting about publicly — their topics, in their words.
video engages better than text, we all know this. and with AI, editing a decent video now costs almost nothing. the wall isn't production anymore. it's briefing. and damn, briefing is hard! "make it feel like this Notion video I love" is not a brief, it's a prayer. A model can't act on it, and neither can I. I've watched the Notion product video probably 14 times and I still can't tell you why it feels expensive. I just know it does. That gap is the real problem. not "can we make a video" but "can we describe the motion we love in words that are actually operational." So here's what I tried for a Linc video I had to ship earlier this year. 1. take a reference video you like 2. normalize to 60fps with ffmpeg so time becomes math (12 frames = 200ms) 3. cut into scenes with PySceneDetect 4. extract evidence frames at 4fps per scene and give an LLM a storyboard of reality, not an MP4 it pretends to watch 5.. then ask one job: scene by scene, strict JSON. every element, entry animation, duration, easing curve, stagger pattern. The output becomes: fadeUp18 = opacity 0→1, translateY 18→0, over 18 frames, cubic-bezier(0.2, 0.8, 0.2, 1). That becomes a brief models can build against! Then, I distilled recurring patterns into a tiny grammar: - popIn18 - staggerIn24 - camera push sparingly - max scale 1.02 and wrote my new script using those primitives as constraints, not as inspiration Last piece was Remotion . Because it's just React, interpolate() and spring() are basically the JSON I already had. My primitives became 40-line components almost 1-to-1...and the script compiled into an mp4! Video attached, I know it could be 10x better but as a non-motion designer using Figma layers + spending few hours it somehow worked out for us! genuinely curious if anyone has a smarter way to do that! happy to share the scripts. Big respect to Jonny Burger and the Remotion team, this framework is wildly underrated. hope it helps 🫶
Apr 2026