Anish Deenadayalan didn’t mind editing videos. In fact, he enjoyed it.
There’s something satisfying about shaping a story, choosing the right moments, and getting the pacing to feel just right.
What he didn’t enjoy was everything around it.
The hours spent scrubbing through footage trying to find the right 30 seconds. Watching the same clips over and over just to make sure nothing was missed. Syncing audio, matching formats, getting everything into place before the real work could even begin. Over time, that part started to stand out. Not because it was difficult, but because it was repetitive, slow, and impossible to avoid.
He knew this from lived experience. Outside of his day job, Anish had been producing music for years, racking up over 1.5 million streams across his releases. Music videos came with the territory. And every single one ran into the same wall: the creative decisions might take minutes, but getting to the point where those decisions could even be actioned would take hours. The bottleneck wasn't making it. It was finding and assembling.
The insight: the bottleneck isn’t creativity
After more than a decade building products at companies like Freshworks and Atlassian, alongside years spent producing music and video on the side, Anish had seen how this played out across very different contexts.
On one end, there was an increasing demand for video. Marketing teams needed more content, educators were expected to produce entire libraries of training material, creators were recording hours of footage every week.
On the other end, the process of turning that footage into something usable hadn’t really changed.
A gaming streamer might record twenty hours of content in a week and then spend several more hours cutting each stream down. An edtech company might need hundreds of videos a month, but their editors could only produce a small number each day. Entire recordings would sit untouched, not because they weren’t valuable, but because no one had the time to go through them properly.
What became clear was that the limitation wasn’t creativity or talent. It was the amount of time it took to get to the right moments in the first place.
Building something to fix his own workflow
The first version of what would become Guin didn’t start as a company. It started as a way to make this process less painful.
Anish began by building a soundtrack engine, something that could analyse a video and automatically generate music that matched what was happening on screen. To make that work, he had to go beyond basic metadata or transcripts and build something that could actually understand the video itself. Who was speaking, what was happening in each frame, which parts mattered.
Alongside the soundtrack engine, there was a simple interface that allowed you to search through footage. You could ask for a specific moment, find something funny, or pull out a particular scene without manually scrubbing through everything.
When he gave the early version to several teams, the behaviour was consistent. The video search tool was used constantly while the soundtrack feature barely got used. Teams would upload 10 to 15 hours of footage and spend their time searching through it.
That was the signal - the hard part wasn’t finishing the video, it was getting to the right pieces in the first place.
From finding moments to making videos
Once that became clear, the direction followed naturally.
If a system could understand video in a way that allowed you to instantly find the right moments, then it could do more than just surface them. It could start assembling them, take the same understanding and use it to build a first cut.
That became Guin.
Instead of starting with a blank timeline and manually piecing things together, teams could upload raw footage, describe what they wanted, and receive a structured first version of the video. The system selects clips, manages transitions, applies brand elements, and produces something that is already usable, whether that’s for publishing or further refinement.
For one of their early customers, an edtech company producing hundreds of videos each month, the difference showed up quickly. Work that used to take days of manual effort could run overnight, with first cuts ready by the time the team came back in the morning.
The role of the editor didn’t disappear. It changed. Less time was spent digging through footage, and more time was spent shaping the final result.
A founder who understands both sides
Guin sits at the intersection of two things Anish has spent years doing.
On one side, he has a proven track record of building and scaling products. He grew Freshchat to $13M ARR at Freshworks, and before that, built and sold his first startup, Frilp, which was acquired by Freshworks. On the other, he has spent years making music and producing video content himself, building an audience and working through the same editing workflows the product is now designed to improve.
That combination shows up clearly in how Guin is being built. It’s deeply technical, but grounded in how people actually work day to day.
The team reflects that as well. A small group of highly technical builders working on the core product, alongside a layer of video editors who use Guin every day as part of delivering work for customers. Their feedback feeds directly into what gets built next, which means the product evolves in line with real workflows rather than assumptions.
Building what video production becomes next
Today, Guin is focused on a specific part of the workflow, turning raw footage into structured, on-brand videos without the usual time overhead. But the direction it’s heading is broader than that.
In the near term, the team is building toward a production agent that can take a script, process multi-camera footage, assemble an edit, and deliver finished outputs at scale. For larger customers, that means processing dozens of videos overnight. For smaller teams, it means being able to generate content on demand without needing a full production setup.
Over time, the ambition is to become the default way teams produce video. The same way design teams rely on Figma or product teams rely on Notion, something that sits at the centre of how work gets done.
Rethinking what limits video
Right now, the amount of video a team can produce is tied to how much editing capacity they have. Time, budget, and headcount all set the ceiling.
Guin changes that equation.
When the work of getting from raw footage to a first cut becomes instant, the constraint moves. Teams stop thinking about how much they can realistically edit and start thinking about how much they can create.
From there, things start to shift. Video stops being something that’s planned weeks in advance and produced in batches and it becomes something that can keep up with the pace of the business.
A webinar turns into clips the same day, a training session becomes a full course overnight, and a single recording turns into weeks of content without adding more people to the process.
And over time, that compounds - teams that can move that quickly don’t just produce more video, they communicate differently, experiment more, ship more ideas and learn faster.
As the gap between recording something and publishing it continues to shrink, video stops being a heavy lift altogether. It becomes as natural as writing a document or sending a message.
And when that happens, the question isn’t how much video a team can produce, it’s what they do with that freedom.
The ask
If you’re a marketing team, edtech company, or creator sitting on hours of raw footage with no clear way to turn it into content quickly, the team at Guin would love to talk.
You can reach out directly or learn more at https://guin.ai
Watch them pitch at Demo Day
When: Thursday, 30 April @ 7:00 PM (pre-party starting at 5 PM)
Where: Carriageworks (at the close of Blackbird's Sunrise Festival)
What: Pitch night (19 companies)
Tickets: Grab your ticket here
