AI Demo & Explainer Videos · Canada

Narrated product demos and animated explainers, produced with AI

Every video on this site was produced with our own pipeline. Browser automation records the real product, a script is written from the feature itself, an on-device voice narrates it, and the edit adds titles, zooms, captions, music and social-media cuts. The result is consistent, fast to update and cheap to redo when the product changes.

Why it matters

Why ai demo & explainer videos needs more than a demo

Product videos go stale the moment the UI changes, and agency production is too slow and expensive to keep up. Treating video as code, with scripted recordings, generated narration and templated edits, means a release can ship with a fresh walkthrough the same week.

What you get

  • Script, storyboard and voice selection
  • 4K and HD masters with captions
  • Vertical and square social cuts
  • Posters, GIF teasers and web-ready files

What we deliver

Our ai demo & explainer videos services

Narrated product walkthroughs

Real product footage recorded with Playwright, with zooms on each action, section labels, subtitles and a clear voice-over.

Animated explainers

Motion-graphics and character-led stories that explain a use case without needing screen footage at all.

Social and launch cuts

16:9, 9:16 and 1:1 versions, GIF loops and posters, plus a posting plan for LinkedIn, X and Reddit.

Feature-release series

A numbered series of short videos covering each feature, rebuilt automatically when the product changes.

Use cases

Where teams use it

  • SaaS feature launches and changelogs
  • Sales enablement and onboarding videos
  • Investor and partner demos
  • Industry-specific use-case explainers
Why RAG demos break on real documents, and how Akurion handles itNarrated explainer that starts with why RAG prototypes fail on large, changing document sets, then shows Akurion product screens: connectors, auto-generated metadata keys, chat filters, the Graph RAG relationship map, cited source pages opened in chat and the MCP playground.
18 questions Akurion answers across teamsAnimated, narrated montage of 18 example questions answered from documents for claims, legal, credit, healthcare, manufacturing, HR and IT teams, each with a short cited answer. Uses illustrative fictional data.
Insider Scanner: open-market insider buying and sellingNarrated walkthrough of the Insider Scanner, which ranks open-market buys and sells by officers and directors by dollar value, filtered by company size and time window. Each trade links to its Form 4, and pre-planned 10b5-1 trades are left out.
Cross-Source Agreement: insiders, Congress and funds in stepNarrated tour of Cross-Source Agreement, which lists stocks where company insiders, members of Congress and large funds are all buying or all selling. Opening a card shows a plain-English write-up and a quarter-by-quarter activity recap next to the share price.

Process

How a project runs

  1. 01

    Discover

    We map the workflow with the people who run it, find the highest-value automation points and agree measurable success criteria.

  2. 02

    Prototype

    A working prototype on your real data in weeks, not months, tested with real users against the agreed criteria.

  3. 03

    Harden

    Security review, evaluation suite, monitoring, permissions and integration with your systems, ready for production.

  4. 04

    Run and improve

    We hand over with documentation and training, or stay on to operate, measure and extend the system.

AI Demo & Explainer Videos: frequently asked questions

Do you use real product footage or mock-ups?

Both. Walkthroughs use real footage from your product, usually on a demo account with sample data. Animated explainers are fully illustrated and need no screen footage.

Whose voice is used for narration?

We use licensed preset AI voices by default. With documented consent, we can also produce narration in your own voice.

Tell us about the process you want to automate.

A 30-minute call is enough to tell whether AI is a fit, what a first project would look like and what it would take to run it in production.