OpenServ ✓

OpenServ (SERV) is AI infrastructure that adds a reasoning layer between your agents and the underlying LLMs, aimed at making agentic workloads reliable, efficient, and auditable for enterprises, banks, and governments.

Its Reasoning Engine wraps model calls in structured reasoning graphs with validation, private inference, execution logs, and added security — addressing the ways raw LLMs fail in production: chained calls that compound cost and latency, prompts that don't enforce structured behavior, and black-box decisions that regulated teams can't trace.

It's positioned as a drop-in: OpenAI- and Anthropic-SDK compatible, so you swap one base URL line and keep your existing agents, with no vendor lock-in and a roughly two-minute integration.

Beyond the API, it offers a builder platform, an SDK and CLI/skills for building agents, x402 services, and a tokenization/launch layer for the "agent economy." The site cites production customers across banking, food, robotics, and DeFi, claiming lower inference cost and near-zero failed calls, though the headline stat figures render as placeholders (0x, 0%).

Access is via API request and enterprise sales rather than self-serve pricing.