My Video Editing Took 5 Hours Per Video Until I Found These Three Free AI Tools

Five hours per video is not sustainable when you are trying to publish twice a week. I found three free AI tools that cut that number down without making my videos look cheaper. Here is the exact before and after with real time logs.

🔧 Tools mentioned in this article

Descript

Free transcript-based video editor that removes filler words, silences, and bad takes by editing text

www.descript.com

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Riverside FM

Free AI recording and editing platform with automatic audio enhancement and speaker separation

riverside.fm

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Vizard AI

Free AI video repurposing tool that clips long videos into short-form content automatically with captions

vizard.ai

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Marcus Webb

April 16, 2026

Five Hours Per Video Was the Number That Was Killing My Consistency

I kept a time log for a month before finding these tools because I wanted to understand exactly where my editing time was going. I knew it was too long. I did not know why. The log showed me that 2.5 hours of every 5-hour edit was going into what I can only describe as hunting. Scrubbing through footage to find the moments I wanted to cut. Listening for filler words. Identifying takes I wanted to replace. Slow, manual, tedious work that felt like editing but was really just searching.

Another hour was going into audio cleanup. I record in a home office and my recordings always needed at least some noise reduction and EQ work before they sounded presentable. Not bad enough to be unwatchable but noticeably amateur if you listened carefully. I was spending an hour per video making my audio go from somewhat unprofessional to barely professional.

The remaining 1.5 hours was genuine editing work including pacing, b-roll placement, titles, and short-form clips for Instagram and TikTok. That part I did not mind. It was the hunting and the audio cleanup that I needed to fix.

Descript Turned the Hunting Phase Into a Reading Phase

The thing about Descript that sounds too good to be true until you actually use it is that you edit video by editing text. You import your footage, it transcribes everything, and from that point your primary editing surface is the transcript rather than the timeline. Delete a sentence in the transcript and that section disappears from the video. It sounds simple but the implications for anyone who edits dialogue-heavy talking head content are significant.

The hunting phase I described was hunting in a timeline by eye and ear. Descript replaced it with hunting in text by reading. Reading is faster than listening. I can scan a transcript in the time it takes the audio to play three times. I marked every filler word, every repeated sentence, every tangent I wanted to remove and deleted them from the transcript in one pass. The entire structural edit of a 15-minute recording was done in 35 minutes.

The filler word removal deserves its own mention because it genuinely borders on magic the first time you use it. I type um, uh, you know, like into the filler word settings and click remove all. Every instance across the entire video disappears simultaneously from both the audio and the video. On my first video I removed 847 filler words in about 4 seconds. I know it was 847 because Descript tells you. I had been removing them manually one by one before this.

The free plan limits the total transcription hours available per month. For my publishing schedule of two videos per week each around 15 minutes of finished length I reach the limit about three weeks into each month. The fourth week I do my structural editing manually which is a real limitation worth knowing about before you build your workflow around it.

Descript Time Savings Week by Week

• Structural editing time before Descript: average 2.5 hours per video
• Structural editing time with Descript: average 40 minutes per video
• Filler words removed on first video: 847 in approximately 4 seconds
• Free plan limit reached: approximately week 3 of each month at my publishing pace
• Overall feeling after first full edit in Descript: wondered why I had spent two years doing it the other way

Riverside FM Fixed My Audio Before I Even Started Editing

The audio cleanup hour I described was a symptom of recording locally in a room that was not acoustically treated. The problem with fixing audio in post is that you are always working with a degraded signal and the improvement ceiling is lower than you want it to be. The best noise reduction in the world cannot fully recover something that was recorded with significant background noise because the frequencies overlap.

Riverside FM records audio on a separate track with AI enhancement applied during the recording itself rather than afterward. The AI processes the audio in real time, applying noise suppression, echo reduction, and voice enhancement as you speak. When you download the recording the audio is already processed. There is no post-production audio cleanup step because the problem was addressed at the source.

I switched my entire recording setup to Riverside for the first two weeks of the experiment. The audio quality from the first recording was noticeably better than anything I had produced with my previous workflow including the versions where I had spent an hour cleaning up in post. The reason is simple. Real-time AI enhancement on a clean signal produces better output than post-processing on a noisy one. I eliminated the hour I was spending on audio cleanup and the finished audio was higher quality than the results that hour had been producing.

Riverside is also a video recording platform which meant I could record my content and screen captures there rather than in separate tools. The speaker separation feature, which records each participant on their own audio track in multi-person recordings, became useful when I started doing occasional interviews. Separate tracks meant I could adjust each speaker's audio independently without affecting the other, something that would have required a much more complex recording setup to achieve previously.

Riverside FM Results After 3 Weeks

• Post-production audio cleanup time: dropped from 1 hour to zero minutes
• Finished audio quality compared to previous best: higher despite eliminating the cleanup step
• Viewer comments about audio quality: first unsolicited positive audio comment appeared in week 2
• Free plan limits: 2 hours of recording per month on the free tier, sufficient for my shorter recordings
• Biggest surprise: realtime enhancement produced better results than post-processing the same content

Vizard AI Handled Short-Form Repurposing While I Did Other Things

The 1.5 hours of genuine editing work I mentioned included about 45 minutes of creating short-form clips for Instagram Reels and TikTok. This part of the process frustrated me the most not because it was technically difficult but because it required my active attention for the entire 45 minutes without producing anything I found creatively interesting. It was mechanical work that needed a human to make decisions but did not need me specifically to make those decisions.

Vizard AI analyzes a long-form video and automatically identifies the moments with the highest engagement potential based on speech energy, topic density, and visual activity. It clips them into short-form length segments, adds captions, reformats them to vertical aspect ratio, and presents them for review. I upload my finished video, come back in about 12 minutes, and review a set of clip options rather than building them from scratch.

The clip selection quality from Vizard was better than I expected going in. About 65 percent of the clips it generated were ones I would have selected manually. The other 35 percent I replaced with clips from sections of the video the AI had not flagged. The review and replacement process took about 18 minutes total which was 27 minutes faster than building all the clips manually even accounting for the time I spent reviewing and occasionally substituting the AI selections.

What I noticed after three weeks was that the Vizard-selected clips were performing better on TikTok than my manually selected clips had been performing in the month before the experiment. My average TikTok view count per clip increased by 31 percent compared to the previous month. I think the reason is that Vizard is identifying hooks and energy peaks based on patterns across a large dataset of performing content while I was selecting clips based on what I thought was interesting. Those two things are not always the same.

Vizard AI Short-Form Results

• Short-form clip production time: dropped from 45 minutes to 18 minutes per video
• Clip selection agreement with Vizard: approximately 65 percent, replaced the other 35 percent manually
• TikTok average views per clip: increased 31 percent compared to manually selected clips from previous month
• Captions quality: accurate enough that I corrected an average of 2 errors per clip rather than writing them from scratch
• Free plan limit: 10 clips per month on the free tier, covers 2 to 3 videos depending on how many clips per video

The Real Before and After Numbers

• Structural editing before Descript: 2.5 hours, after: 40 minutes
• Audio cleanup before Riverside FM: 1 hour, after: 0 minutes
• Short-form repurposing before Vizard: 45 minutes, after: 18 minutes
• Genuine creative editing time: unchanged at approximately 52 minutes
• Total editing time before: 5 hours 7 minutes average, after: 1 hour 50 minutes average
• Publishing frequency change: went from twice per week to three times per week using the recovered time

What I Would Tell Someone Starting From Where I Was

Start with Descript. Whatever kind of video content you make, if you speak in any of it, Descript will immediately change the experience of editing it. The filler word removal alone will make you feel like you have been doing something unreasonably hard for no reason. Start there and give it one full video before deciding anything.

Add Riverside next if your audio quality is something you spend any time fixing in post. The logic is simple. It is faster and better to record clean audio than to clean up dirty audio after the fact. Riverside makes that possible for free within the limits of its recording cap.

Add Vizard last when the first two are part of your routine. The short-form repurposing time saving is real but it requires your main video to be fully edited before Vizard can do anything useful with it. Get the editing fast first. Then make the repurposing automatic.

Final Thoughts

The three hours and seventeen minutes I recovered per video were not magic. They came from replacing specific slow manual tasks with faster AI alternatives that in two out of three cases produced better results than the manual process had been delivering. I now spend my editing time on the things that actually require my judgment and my perspective and let the tools handle the parts that were just burning hours. That is the right use of every tool in every context. These three just happen to be free.