Why 95% of AI Agent Projects Never Reach Production (And How We're Fixing It)

Source: Dev.to

The Problem

Enterprises are rushing to build AI agents, but the DevOps tooling hasn’t caught up. You’re stuck duct‑taping together:

• Custom orchestration scripts that break under load
• Makeshift observability for debugging agent behavior
• Manual compliance and security configurations
• Infrastructure that doesn’t auto‑scale or self‑heal

Each project reinvents the wheel, forcing AI teams to act as infrastructure engineers.

Solution: Phinite.ai

Phinite.ai provides the DevOps platform that AI agents need—a missing infrastructure layer between your agent code and production deployment.

What Makes It Different?

• No‑code orchestration – Drag‑and‑drop multi‑agent workflows. Compatible with LangGraph, AutoGen, CrewAI—bring your own framework.
• Cloud agnostic – Deploy anywhere: Azure, AWS, GCP, or on‑premises. No vendor lock‑in.
• Enterprise‑ready from day one – Built‑in security, compliance, and role‑based access controls.
• Auto‑scaling & self‑healing – Kubernetes‑native architecture that scales with demand and recovers automatically.
• Observability built‑in – Track agent behavior, debug conversations, and optimize performance without cobbling together monitoring tools.
• 10× faster deployment – What used to take weeks of infrastructure work now takes hours. Deploy agents, not YAML.

Beta Program

We’re opening our beta to developers and teams building agentic AI systems.

Beta Perks

• Free platform credits to build and deploy agents
• Direct access to the founding team
• Influence the product roadmap
• Preferred early‑adopter pricing

Who Should Apply

• Developers building AI agent applications
• Engineering teams exploring multi‑agent architectures
• DevOps professionals managing AI infrastructure
• Anyone frustrated with current agent deployment tools

👉 Apply here: https://app.youform.com/forms/6nwdpm0y