Kritsana is a single-player psychological horror simulation that places players in the role of a reviewer examining retro CCTV footage from 1997 Thailand. The experience centers on anomaly observation mechanics drawn from the patient's recorded tapes, blending simulation elements with tense decision-making as users monitor feeds for irregularities that may stem from mental health issues or something more unsettling.
Gameplay
The core loop requires constant vigilance across multiple camera angles in various locations. Players switch between feeds using keyboard inputs and hold the mouse button to flag any detected anomalies before conditions worsen. Sessions run through the night until 5:00 AM, with failure triggered by accumulating three incorrect reports or allowing four anomalies to remain active at once. Anomalies appear in a range of forms, some progressing through visible stages that alter their appearance over time, while others react directly to observation by changing behavior or position. The retro VHS-style presentation enhances the claustrophobic feel, with every frame demanding close attention to subtle shifts in the environment.
Controls remain straightforward to support focused observation rather than complex inputs. Camera switching happens via A and D keys or the left and right arrow keys, keeping attention on the screens. Reporting relies on sustained mouse input, encouraging deliberate choices instead of rapid clicks. This setup suits short to medium play sessions where precision matters more than speed or reflexes.
Game Modes
The game delivers its content through a single focused observation experience built around sequential nights and locations. Each segment follows the same structure of monitoring feeds, identifying changes, and managing reports until the time limit expires. Progressive elements appear within this framework as anomalies gain complexity across stages, and certain ones demonstrate awareness that influences how they interact with the viewer. No separate competitive or cooperative variants exist, keeping the emphasis on solitary analysis of the footage and the unfolding narrative details.
Story and Setting
Set in Thailand during 1997, the narrative follows psychiatric patient Kritsana who records familiar locations on CCTV to document what he insists are real spirits rather than hallucinations. These tapes reach his psychiatrist, Dr. Thanapat, and the player reviews them to determine the nature of the events shown. The Thai cultural backdrop informs the atmosphere through everyday settings that gradually reveal disturbing elements, maintaining a balance between psychological tension and supernatural implications without relying on overt jump scares.
Key features include a variety of hidden anomalies distributed throughout each environment, with some evolving in multiple phases that increase uncertainty the longer they persist. A subset of these anomalies acknowledge the surveillance and adjust their actions accordingly, adding layers to the observation process. The entire presentation uses authentic retro CCTV and VHS aesthetics to create an immersive, confined viewing experience.
Is It Worth Playing?
Kritsana suits players who enjoy methodical anomaly detection games and atmospheric psychological horror without action or exploration demands. The demo provides a complete first night and location for roughly 10 to 15 minutes of play, allowing direct assessment of the reporting system and anomaly variety before the full release scheduled for Q4 2026. Current feedback from the available demo highlights its tense pacing and cultural authenticity, though the project remains in active development with room for refinements based on player input. Those drawn to simulation-style horror centered on careful monitoring and decision consequences will find the mechanics align closely with that preference, while others seeking faster-paced or multiplayer elements may prefer alternatives. The single-player focus and accessible controls make it approachable for fans of the genre who value atmosphere over complexity.