{"changes":[],"country":"US","description":"Mythic designs analog processing units for AI inference, using a compute-in-memory architecture that stores model parameters in the processor to remove memory bottlenecks. It targets data centers, automotive, robotics, and defense applications needing edge inference. It claims its analog chips are roughly 100 times more energy efficient than GPUs.","domain":"mythic-ai.com","employees":null,"founded":2012,"fundingTotalQuarantined":false,"githubOrg":null,"githubStars":null,"industry":"infra","investors":[],"lat":39.78373,"lng":-100.445882,"location":"USA","name":"Mythic AI","rounds":[{"amountQuarantined":false,"amountUsd":125000000,"currency":"USD","date":"2025-12-01","investors":[],"leadInvestor":null,"source":{"fact":"round","publisher":"crunchbase","retrievedAt":"2026-05-07","status":"attributed","url":null},"status":"attributed","type":"series-d+","url":null}],"slug":"mythic-ai-com","sources":[{"fact":"round","publisher":"crunchbase","retrievedAt":"2026-05-07","status":"attributed","url":null},{"fact":"existence","publisher":"mythic-ai.com","retrievedAt":"2026-05-07","status":"self-reported","url":"https://mythic-ai.com"},{"fact":"description","publisher":"mythic-ai.com","retrievedAt":"2026-05-07","status":"self-reported","url":"https://mythic-ai.com"}],"stage":"series-b+","techStack":[],"totalRaisedUsd":125000000,"updatedAt":"2026-05-07"}