Apace launches DaVinci Resolve AI workflow to search fragmented media archives

Apace Systems unveiled a Blackmagic DaVinci Resolve-integrated AI workflow at IBC 2026 that lets editors search and pull assets from fragmented storage across cloud, tape and offline archives. The company says the system is available now and is designed to keep media private while avoiding recurring SaaS usage fees.

Why it matters: - Media teams often keep footage across disconnected storage systems, which slows discovery and makes archived material hard to use. - Apace’s new workflow aims to make those assets searchable inside DaVinci Resolve, cutting research time and bringing older content back into active production. - The on-premise model is designed to reduce variable cloud costs and avoid per-token AI billing.

What happened: - Apace Systems announced a Blackmagic DaVinci Resolve integrated AI workflow at IBC 2026 in Amsterdam on Sept. 3, 2026. - The workflow is built around DataManager AI, which appears as a native panel inside DaVinci Resolve. - Apace says the integration is available now. - The company says more information and a demo are available at the company’s website.

The details: - The system unifies data across on-premise storage, cloud platforms, LTO tape and offline media into a semantic searchable repository for DaVinci Resolve timelines. - Supported cloud tiers include Wasabi, iDrive and AWS, along with local storage silos and air-gapped assets. - Editors can search, tag and get clip recommendations without leaving Resolve or switching applications. - The panel is intended to fit color, cut and Fairlight workflows. - Semantic search covers faces and people, objects, visual scenes, spoken audio and on-screen text. - Matching clips can be dropped directly into the active DaVinci Resolve project timeline. - Context-aware agentic AI is designed to scan thousands of hours of archival footage and recommend relevant clips based on project context and story prompts. - Apace says the system uses on-premise CapEx GPU infrastructure instead of recurring SaaS token fees. - The workflow also produces frame-accurate proxies for production locally or remotely. - The company says proprietary footage and metadata remain inside private infrastructure and that there is zero training or data harvesting on user content.

Between the lines: - The launch targets a long-standing media operations problem: AI tools are only useful if they can access the full archive, not just a single storage bucket. - Apace is positioning privacy and predictable costs as its main differentiators against cloud-first AI workflows. - The Resolve integration suggests the company wants search and discovery to feel like part of the edit, not a separate AI layer.

What’s next: - Editors and media teams can begin using the integration immediately, with adoption likely tied to how well it handles large legacy archives in real production workflows. - Apace will likely push the product as a way for broadcasters, enterprise video teams and archive managers to activate older media without moving it all into a single cloud stack.

The bottom line: - Apace is betting that AI in post-production will win on privacy, cost control and direct timeline access, not just on model capability.