Context should persist
AI systems should not have to reconstruct organizational context from scratch every time a model, client, or session changes.
Founder story
Zdravo started from a simple infrastructure problem: AI agents can generate answers and take actions, but organizations still need durable context, explicit controls, and evidence for what happened.
The starting point
The idea behind Zdravo is less about making one model smarter and more about giving organizations a durable layer around the models they already use. Memory, retrieval, identity, policy, decisions, and evidence belong in infrastructure that can outlast any individual model or client.
AI systems should not have to reconstruct organizational context from scratch every time a model, client, or session changes.
Authentication is not authorization. Zdravo binds identity, evaluates policy, and records explicit ALLOW, DENY, or ASK_HUMAN outcomes before protected execution.
Decisions, observations, and audit records should make an agent action inspectable after it happens, not just visible in a log dashboard.
What exists now
The current implementation includes PostgreSQL and pgvector persistence, organization and governed-agent identity binding, MCP authorization, policy decisions, fail-closed governed execution, atomic observation completion, row-level security, and audit/provenance structures. The architecture page documents the current boundaries in more detail.
Read the architectureZdravo is still being built. The goal is not to make AI look more autonomous. It is to make the systems around AI more durable, inspectable, and governable.