CortexOps provides AgentFlow, a native orchestration platform that lets enterprise teams design, provision, and monitor complex multi‑agent AI workflows through a visual node‑based editor. The platform offers granular observability, token‑budget controls, and an extensible tool registry for integrating search, code execution, web scraping, and internal APIs, enabling reliable, cost‑controlled production of autonomous AI agents.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises struggle to move multi‑agent AI prototypes into reliable production because workflows become fragile, execution is opaque, and costs can explode due to uncontrolled token usage.
Solution
CortexOps offers AgentFlow, a native orchestration platform that provides a control plane for provisioning, routing, and monitoring autonomous AI agents at scale. Users design complex, multi‑step workflows with a visual node‑based editor, assign custom system prompts and toolsets to each agent, and enforce execution constraints such as token budgets and approval steps. The platform delivers granular observability, logging execution times, token consumption, and step‑by‑step outputs, enabling deterministic and secure operation of thousands of agents. By integrating an extensible tool registry, AgentFlow connects agents to search, code execution, web scraping, and internal APIs without custom glue code, turning experimental prototypes into production‑ready business processes.
Target Audience
Primary customers are enterprise engineering and operations teams that need to deploy scalable, reliable multi‑agent AI solutions for use cases such as support triage, data research, and code review automation.
Features
- Visual workflow editor with node‑based design for branching logic and agent handoffs
- Agent provisioning with custom system prompts, personas, and dedicated toolsets
- Extensible tool registry supporting search, code execution, web scraping, and API integrations
- Granular observability including per‑node execution logs, latency metrics, and token usage analytics
- Execution controls such as sandboxing, token budgets, and approval nodes to prevent runaway costs
- API and dashboard interfaces for triggering workflows and reviewing results in real time