Vithia is a verifiable runtime for long-horizon agents. Instead of treating a long conversation or task history as one opaque context window, Vithia turns work into independently addressable evidence objects (FCOs) connected in a temporal evidence graph (FCG). Each cycle records the source event, atomization, policy/field state, candidate Golden and Dark paths, the exact bounded context shown to the model, and the successor state. Canonical object hashes are appended to Merkle/MMR breakpoints so a later agent can reconstruct what existed and what the model actually saw without claiming that a hash proves the truth of the content.
The demo executes a real cold restart: the agent process is killed, then reconstructs the same bounded context and custody state from the persisted object store rather than the original conversation. We also integrated sponsor lanes: Liquid AI for bounded-context inference, Nimble for external web evidence, RawTree/Tinybird for persistent telemetry, and Black Forest Labs for generated visual evidence. LongMemEval-V2 provides the benchmark lane. The goal is durable, inspectable agent state that can grow in total evidence while keeping active context bounded.
