Raising Seed Funding for a Production-Grade AI Execution Platform

 I am a solo founder and hands-on software architect building a deterministic AI runtime for reliable, distributed and agentic workflow execution. The platform provides durable DAG orchestration, deterministic replay, crash recovery, configurable retention, policy-driven execution, plugin-driven extensibility, multi-tenant isolation, distributed observability, decision ledgers, execution forensics and Kubernetes-native runtime hosting. It is designed to ensure that complex AI workflows and recursive agent executions can survive process failures, pod termination, retries, redispatches and high concurrency without losing execution state, duplicating work or crossing tenant boundaries. High-concurrency execution and crash recovery have already been validated through real adversarial scenarios involving multiple tenants, parallel workflows, external runtime processes.