Use AI to scout locations in four steps: describe the scene or upload the script to an agent, have it pull candidate real-world location plates from the internet, filter the returns against your shootability criteria (light, geography, story logic), then pre-visualize the chosen plate as a generation reference for the actual shot. The invideo agent runs this loop end-to-end.
Start by giving an agent the scene context — either the full script or a prose description of the location beat (era, geography, time of day, mood, action). The invideo agent is an agentic video tool that holds project context across the whole production, so once the script is loaded, every location request inherits character, story, and visual-style continuity rather than being prompted from scratch.
Next, ask the agent to pull real-world reference plates from the internet that match the brief. In a documented one-take production where a character was carried across multiple cities, the director used exactly this loop: "Agent 1 referenced these images off the internet for me, and I picked the ones I liked." The agent returns a set of candidate landmark and environment images; you select. This is the human-in-the-loop step — the agent surfaces options, you make the directorial call.
Then filter the candidates against shootability for an AI pipeline: does the lighting match the scene's time of day and color script, does the geography read on camera, does the location carry the story beat, and is the framing usable as a reference plate. Treat references in batches rather than as one master image — separate plates by spatial logic, lighting, and color theory, and tell the agent explicitly what to adopt from each and what to ignore. "I told it what to take and just as importantly, what to leave out."
Pre-visualize before you commit. Spin up a storyboard sub-agent to render the selected plate as a frame in your film's style, with your character and lighting locked in — this is the cheap step that catches a wrong location before you spend video credits. Image generation is inexpensive on invideo, so generate grids of options per location rather than single frames, then extract the winning panel as your continuity anchor for that scene.
Finally, route the locked plate into video generation. Pass the location image alongside your character sheet and style references to Seedance 2.0 reference-to-video — it carries location, character, and camera context across clips, which is what makes continuous one-take sequences across multiple locations possible. For multi-segment journeys, clip the end of each generated segment and re-upload it as the next segment's reference so camera movement, framing, and atmosphere stitch seamlessly. invideo holds all current video models (Runway, Veo, Kling, Seedance 2.0) under one agent, so the agent routes each shot to the right model rather than you switching platforms.
For scale: a documented short film with multiple international locations and a long-take sequence ran ~$5,000 across four people in a 5-day sprint; a 2-minute brand promo with location-driven scenes ran $1,500 in 3 days versus a $100,000–$500,000 traditional equivalent. Distributed teams work fine here — "All of us are working with Agent 1, so it doesn't really matter where we are" — because the location library and references live in the agent's context, not on any one machine.
Beyond the scout-and-generate loop, two practical filters to add to the brief: golden-hour and time-of-day light timing (so candidates match your scene's lighting plan) and an explicit story-logic check on each location, not just aesthetics.
Watch some of these to see what works for you:
Agent 1 referenced these images off the internet for me, and I picked the ones I liked.
— Hridaye, invideo's creative director