CNT Tech backs AI video startup Damgara in early-stage round
What's the deal? Accelerator CNT TechDealroom has a profile for this one. Try Dealroom → has made an early-stage investment in DamgaraDealroom has a profile for this one. Try Dealroom →, a Korean startup building an AI platform that automates video pre-production. The amount was not disclosed by mutual agreement.
What does Damgara do? Founded in 2025, the startup develops STORYSYNC Pro, which manages planning, scriptwriting, storyboarding, shot design, video generation, and editing in a single workflow. Its founders bring roughly 20 years of experience in commercial video and media art.
How was it found? CNT Tech discovered Damgara through the 2026 Scale-up Accelerating program, run by the accelerator and organised by the Chungnam Content Agency. It reviewed the business model and technology before deciding to invest.
How does the product work? STORYSYNC Pro uses a four-agent system — playing writer, director, cinematographer, and producer — to cross-check narrative and staging, cutting the character and background drift common in AI video. Its PromptAdapter engine automatically picks the best model for each task from options such as Seedance 2.5 and Kling 3.0Dealroom has a profile for this one. Try Dealroom →, helping producers manage costs.
Traction: The platform won a CES 2026 Best of Innovation Award. Damgara says its own projects cut costs by more than 95% and production time by about 90% versus manual methods, though results vary by project. It has run paid proofs of concept with video producers and public and cloud partners, and signed letters of intent.
What's the money for? Damgara plans to commercialise the platform as B2B SaaS and pursue follow-on scale-up steps, including pre-TIPS. "We will grow into a global platform that provides film-expert-level workflows to small producers and creators struggling with staff and budget," deputy chief executive Park Kwan-yong said (translated from Korean).
The signal: As generative video tools multiply, the harder problem is stitching them into a reliable production pipeline. Investors are increasingly backing workflow layers that orchestrate multiple models rather than the models themselves.
Read more: venturesquare.net
Image credit: Generated with Gemini
