A startup brand film for EulerESG. Responsible AI, applied to ESG reporting.
EulerESG won the People's Choice Award at the 2025 UNSW SDG Showcase. This video positions the tool as a credible, scalable solution for ESG analysis.
Built by UNSW researchers with Data61 (CSIRO), it uses LLMs and dual-channel retrieval to extract and verify ESG metrics, hitting up to 0.95 accuracy against frameworks like SASB.
The video does not teach the technology. It makes the right people want to.
01. Explain the problem EulerESG addresses, clearly.
02. Show why the work matters to society, regulators, and reporting.
03. Explain how the system works in plain terms.
04. Show the real-world impact it can create.
The aim is for the video to be informative, credible, engaging, and accessible. Memorable, without feeling like a sales pitch.
Responsible AI bridges the gap between ESG reporting and real, SDG-aligned action.
The video speaks to four audiences. Messaging skews toward regulators and compliance leadership. These are the people most likely to act on what they see.
Set up the world. Make the stakes felt.
ESG reports run hundreds of pages across SASB, GRI, and CSRD. Dense, inconsistent, easy to miss. Auditors and regulators are expected to call them anyway.
Kino opens. Calmly, plainly, she names the problem.
Introduce EulerESG. Anchor it in research.
The UNSW academic lead grounds the project. Peer-reviewed, built with Data61. Designed to do what humans cannot do at scale, with the rigour humans demand.
Kino explains the mechanism in plain terms: read the report, find what matters, check it against the standards, show the work.
Move from feature to consequence.
A team member or Data61 collaborator picks up the thread. What used to take a week takes minutes. Inconsistencies surface automatically.
Specifics over slogans. Up to 0.95 accuracy against frameworks like SASB. Cross-company benchmarking. Source-linked verification.
Land the meaning. Show the real-world impact.
Kino closes. The work is about better decisions on the things that matter. Responsible AI, doing something useful in the world.
The tone is informative and credible. Not a pitch. The viewer should leave understanding what EulerESG does, why it exists, and what it can change.
Each speaker has a clear role in the story. Interview questions are designed to draw out unscripted, real responses. Primary questions are the ones we most need on tape. Follow-ups are there to deepen a thread if the conversation opens up. Each speaker should aim for around 20 minutes of recorded interview.
Sets the vision. Establishes credibility at the top of the story.
"What is EulerESG, and why does it exist?"
"Why is now the right moment for a tool like this?"
"What does responsible AI mean in the context of this work?"
"Why was research collaboration with UNSW and Data61 important to building this?"
"What does success look like for EulerESG over the next two to three years?"
Anchors the founder-led narrative. Carries the why, the mechanism, and the closing thought.
"What problem were you trying to solve when you started building EulerESG?"
"In one sentence, what does EulerESG actually do?"
"How does the system work in plain terms? Walk us through what happens when a report comes in."
"Why does this work matter beyond the technology?"
"What surprised you most about building EulerESG?"
"What is one thing you wish people understood better about ESG reporting?"
Brings the work to life from the inside. The hands-on perspective.
"What does your day-to-day look like working on EulerESG?"
"What part of EulerESG did you work on, and why did it matter to you?"
"Can you describe a specific problem you solved that you are proud of?"
"What kinds of ESG data does the system handle that you couldn't handle manually before?"
"What is the most interesting thing you have learned working on this project?"
National-level validation. Confirms the work is taken seriously beyond UNSW.
"Why did Data61 want to collaborate on EulerESG?"
"What does success look like from Data61's side?"
"How does work like this contribute to Australia's broader responsible AI agenda?"
"What makes a partnership between a national research agency and a university research team work?"
"Where do you see ESG analysis and AI heading over the next few years?"
Confident, considered, human. Real people, real environments. References below set the tone.
Mid-shot, naturally lit, real campus environments. Story-paced cuts.
Whiteboard work. Two researchers reviewing a screen. Documentary instinct.
The dashboard pulling data. Highlights snapping onto extracted metrics.
A clean motion-graphics build of the four-stage diagram. Used once, in the right moment.
Exteriors and interiors that anchor the work in UNSW without leaning on logos.
Cinematic colour, natural light, soft contrast. Within UNSW guidelines.
Cast and suggested location types. Final spots will be scouted with the team.
Three filming locations across the partnership. Each environment plays a defined narrative role.
Shot list broken out by filming day. Each day has a defined narrative purpose, cast, and location. Built to give us the coverage needed for the hero edit, the 30 to 60 second cut-down, and a library of supporting clips.
A tighter edit drawn from the same shoot. Built for social platforms and short-form distribution. The structure: name the problem, show the answer, deliver the meaning.
An invitation to learn more about the work and connect with the team.
Working backwards from end of May. The location-by-location structure of the production reflects the partnership the video is about.
Confirm cast, lock filming days, gather materials, finalise questions.
Three filming days. Thu 14 May afternoon (UNSW, time TBC). Fri 15 May 13:00-15:00 (Data61 Marsfield). Tue 19 May afternoon (EulerESG City Office, time TBC).
First cut. Sound, colour, motion-graphics build. V1 review.
Revisions actioned. Hero locked. Optional cut-downs delivered.
The decisions and confirmations required to move into production. Roughly in order. None are blockers individually, but together they set the schedule.