Video
AI Explainer Video on Martini
B2B SaaS founder building a 60-second homepage explainer for the new product launch. Voiceover script paste in, scene-by-scene image generation across Nano Banana 2 and Flux, image-to-video chains across Sora 2, Veo, Kling 3, Seedance 2, and Runway Gen-4, ElevenLabs voiceover, lip-sync where the explainer features a presenter — all on one canvas. For real product UI, capture actual screen-recording rather than fake-looking model output.
What this feature solves
Explainer videos are the homepage moat for most B2B SaaS founders. A 60-second clip on the landing page that walks the visitor through the problem, the solution, and the call-to-action lifts conversion materially over text-only marketing — but producing one is expensive. Hiring an explainer-video studio runs $5,000 to $50,000 and weeks of turnaround. DIY-ing it in Camtasia or screen-recording tools produces a video that looks like an in-house demo, not a product launch. The founder needs production polish without a production budget.
The other half is iteration cost. The product changes, the messaging changes, the pricing changes — and a $20,000 explainer video commissioned in Q1 is stale by Q3. Re-engaging the studio for a refresh costs a fraction of the original but still slows the founder down by weeks. Tab-based AI tools that promise explainer-video generation produce one-off clips with limited control over scenes, voice, pacing, and brand consistency — so the second iteration is no faster than the first.
And there is the literal-vs-conceptual line. For B2B demos involving real product UI, the right answer is screen-recording. AI-generated 'fake UI' looks fake, and the audience notices. AI explainer is at its strongest for concept-level education — abstract concepts, problem-state animations, story-driven product positioning — paired with actual screen-recording for the literal product walkthrough. A workflow that pretends the AI can replace screen-recording is shipping low-fidelity output; the honest workflow chains AI conceptual scenes with real screen capture.
Why Martini is different
Martini handles the explainer-video chain on one canvas. The script lives as a text node — paste the voiceover, segment by scene. Each scene becomes a parallel chain on the canvas: image generation (Nano Banana 2 for branded scenes, Flux for high-detail concept), image-to-video (Sora 2 for long-take establishing motion, Veo for product context, Kling 3 for cinematic transitions, Seedance 2 for reference-faithful clips, Runway Gen-4 for editorial polish), voiceover (ElevenLabs node generating the line for that scene), and lip-sync (when the explainer features an avatar or presenter speaking). The chain is explicit; every scene's lineage is auditable.
Multi-model fanout for hero scenes, single-model for the catalog of scenes. For the opener and the close — the two scenes that anchor the video's tone — fan across Sora 2, Veo, Kling 3, Seedance 2, and Runway Gen-4. Pick the strongest take per anchor scene. For the middle eight scenes, lock the winning model and run them through the chain. The first version of a 60-second explainer comes together in a few hours of canvas work; the iteration cycle (refresh the script, re-render) is minutes rather than weeks.
Downstream chaining handles the editor handoff. Sequence-builder nodes assemble the scenes with the voiceover aligned and the music bed (from a Suno node or a brought-in score) layered. The export ships frame-rate-clean and codec-clean for Premiere Pro, DaVinci Resolve, and Final Cut Pro. For B2B explainers featuring real product UI, the canvas accepts screen-recording captures as image or video nodes that drop into the sequence alongside AI-generated conceptual scenes — the honest hybrid workflow that produces a credible homepage explainer.
Common use cases
B2B SaaS homepage 60-second explainer
Founder ships a 60-second concept-level explainer paired with screen-recording for the actual product walkthrough — homepage hero ready in a day.
Curriculum walkthrough for an education company
Education team produces a 90-second explainer for each new course unit — concept animation paired with voiceover and on-screen captions.
Internal compliance or HR training video
HR team builds compliance training explainers for onboarding flows — voiceover-led, scene-by-scene, multi-language with ElevenLabs.
Product launch explainer for a Series A announcement
Founder pairs a launch announcement on social with a 60-second explainer that walks through the problem, the wedge, and the early customer story.
Concept-level fundraising explainer for the investor deck
Founder embeds a 30-second concept video in the pitch deck appendix that walks the partner through the market wedge before the full meeting.
Customer success or onboarding educational series
Customer success team produces a series of short concept explainers that walk new customers through specific feature concepts before the actual product walkthrough.
Recommended model stack
sora-2
videoLong-take establishing motion and cinematic opener scenes for the homepage hero explainer.
google-veo
videoProduct-context motion and clean B2B concept scenes that survive the homepage compression.
kling-3
videoCinematic transitions and editorial concept scenes for higher-production explainer videos.
seedance-2
videoReference-faithful image-to-video chains for branded scenes anchored to a still.
runway-gen4
videoEditorial polish for the closing scene and call-to-action moments in the explainer.
How the workflow works in Martini
- 1
1. Paste the voiceover script as a text node
Drop the 60-second voiceover script onto the canvas as a labeled text node. Segment by scene — opener, problem, solution, customer story, call-to-action.
- 2
2. Build the per-scene image generation chain
Each scene becomes an image node — Nano Banana 2 for branded scenes, Flux for concept illustration. Generate the still that anchors each scene.
- 3
3. Fan the opener and close across multiple video models
For the opener and the closing scene, fan the still across Sora 2, Veo, Kling 3, Seedance 2, and Runway Gen-4 image-to-video nodes. Pick the strongest take per anchor scene.
- 4
4. Lock the winning model for the middle scenes
For scenes three through eight, lock the strongest model (often Veo for B2B concept work) and run image-to-video through the chain at consistent length and motion language.
- 5
5. Generate the voiceover with ElevenLabs
Drop an ElevenLabs node, paste the per-scene script, pick a voice, and generate. The voiceover lands aligned to the script structure.
- 6
6. Sync screen-recording captures for real product UI
For B2B explainers showing actual product UI, drop screen-recording captures onto the canvas as image or video nodes. Splice them into the sequence alongside the AI-generated conceptual scenes.
- 7
7. Sequence and export to NLE
Wire all scenes plus voiceover plus music bed into the sequence-builder node. Export NLE-clean for Premiere, Resolve, or Final Cut Pro.
Example workflow
Sara is the founder of a B2B compliance SaaS launching a homepage explainer in advance of the Series A announcement. She opens a workspace canvas and pastes the 60-second voiceover script as a text node — opener (the compliance problem in finance teams), problem (the manual reconciliation pain), solution (her platform automating the workflow), customer story (a beta customer reducing audit prep from weeks to days), call-to-action (book a demo). For the opener and close, she fans across Sora 2, Veo, Kling 3, Seedance 2, and Runway Gen-4; Sora 2 wins the opener (long-take establishing finance-office motion), Runway Gen-4 wins the close (editorial product-pulse moment). She locks Veo for the middle scenes (problem, solution, customer story) and chains stills from Nano Banana 2 (branded illustration of finance team and dashboard concepts) into Veo image-to-video nodes. For the actual product UI demo segment in the middle, Sara drops a 12-second screen recording of the live product onto the canvas and splices it into the sequence. ElevenLabs generates the voiceover with a calm warm voice. The music bed is a Suno-generated upbeat-but-restrained instrumental. Sequence builder assembles the scenes; NLE export to Premiere ships the cut. The homepage publishes the explainer with the Series A announcement Tuesday morning.
Tips and common mistakes
Tips
- Use real screen-recording for actual product UI. AI-generated fake UI looks fake; the honest hybrid workflow combines AI conceptual scenes with real screen capture.
- Fan out only on the opener and close. Lock the winning model for the middle scenes; the iteration budget belongs to the anchors.
- Match motion language across scenes. Different models have different motion personalities; one locked model for the middle keeps the explainer cohesive.
- ElevenLabs handles the voiceover; review the take for pacing and emphasis, then re-generate the lines that need a different read.
- Save the canvas as a series template. Curriculum, customer success, and product-update explainers next quarter inherit the chain.
Common mistakes
- Generating fake-looking product UI for B2B explainers. Use actual screen-recording for the product walkthrough; reserve AI for concept-level scenes.
- Promising auto-translation across languages. Voiceover dubbing across languages still benefits from a human reviewer; ElevenLabs multi-language is a tool, not a finished translation.
- Skipping the disclosure on AI-generated content for corporate compliance, education, or regulated contexts. Disclose AI generation where required by policy or regulation.
- Mismatched frame rates and aspect ratios across scenes. Most B2B explainers ship 1080p 16:9 at 30fps — match the spec across every scene before sequencing.
- Treating the AI explainer as a substitute for a real production studio on flagship campaigns. For brand-defining homepage videos at high-spend B2B contexts, a real director and DP still win on storytelling and final polish.
Related how-to guides
Related models and tools
Tool
AI Lip Sync
Lip-sync tools on Martini for syncing voice and dialogue to portraits and video.
Tool
AI Video Frame Extraction
Extract frames from video for reference and image-to-video workflows.
Provider
OpenAI
OpenAI's GPT Image and Sora video model workflows available on Martini.
Provider
Google's Veo video, Imagen image, and Nano Banana model workflows on Martini.
Provider
Kling
Kling 3, O3, and Avatar video model workflows on Martini.
Provider
ByteDance
ByteDance's Seedance video and Seedream image model families on Martini.
Provider
ElevenLabs
ElevenLabs voiceover, lip-sync, and voice cloning workflows on Martini.
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Related docs
Related reading
Comparisons
Frequently asked questions
How is this different from a talking head video?
Explainer videos are educational, B2B-demo, and concept-driven content typically paced by voiceover with abstract or illustrative visuals — distinct from a single host on camera (talking head) or a synthesized presenter avatar. Explainer often combines AI concept scenes with real screen-recording for the product walkthrough; talking head is the host alone speaking to camera; avatar video is a fully synthesized presenter. Different content types, different production wedges.
Can I use this for a B2B product walkthrough?
Use AI for the concept-level scenes (the problem, the wedge, the customer outcome) and use real screen-recording for the literal product UI walkthrough. AI-generated fake UI looks fake — the audience notices. The honest hybrid workflow drops screen-recording captures into the canvas as image or video nodes alongside the AI conceptual scenes; both ship as one cohesive explainer.
Which model is best for explainer videos?
Different scenes favor different models. Sora 2 leads on long-take establishing opener motion. Veo handles B2B concept scenes that survive homepage compression cleanly. Kling 3 brings cinematic transitions for higher-production explainers. Seedance 2 holds reference-faithful chains for branded scenes. Runway Gen-4 delivers editorial polish for closing call-to-action scenes. Fan out across all five for the anchor scenes and lock the winner for the middle.
How do I generate the voiceover and sync it to the video?
Drop an ElevenLabs node on the canvas, paste the script line by line, pick a voice character that matches the brand tone. The voiceover generates aligned to the script segments. The sequence-builder node aligns the voiceover with the visual scenes; for finer alignment, export to your NLE and refine in the timeline.
Can I produce multi-language explainer videos?
ElevenLabs supports multi-language voiceover generation, which makes localized variants of the same explainer fast to produce. Caveat: dubbing across languages still benefits from a human reviewer to catch tone, idiom, and pacing nuances. For mission-critical localized content (compliance, regulated education, official corporate communications), pair the AI voiceover with a native-speaker review pass before publishing.
Should I disclose that the explainer is AI-generated?
For corporate compliance, regulated education, or formal investor materials, disclosure is often required by company policy or regulation. For homepage marketing, customer success content, and general B2B explainers, disclosure is increasingly expected even when not required — and tends to earn trust rather than lose it. Add a small "AI-assisted production" note in the credits or video description as the default posture.
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