How a Cloudify agent system works
One accountable system, not a pile of tools. Six parts, each doing a specific job, all built and operated by us on top of the software you already run.
One agent is a demo
A single agent with a good prompt will impress a room. It will also forget the deal details, invent a policy, and give two different answers to the same question in a week. That is not a model problem. It is an orchestration and memory problem.
Production work needs coordination, grounded knowledge, scoring, and a way to turn failures into fixes. Those are the four things a demo never has, and they are the four things below.
The six parts
Agent Teams
Specialized agents that hand off work to each other. Sales follow-up, document processing, reporting, customer operations. Each agent does one job well instead of one agent doing everything badly.
A single general-purpose agent fails for the same reason a single general-purpose employee fails at scale. Scope creep destroys reliability. Narrow agents are easier to score, easier to fix, and easier to trust with a specific class of work.
AI Manager
A manager agent routes every task to the right agent and pulls the right knowledge from your company brain. The correct context loads on every task, not only when someone remembers to ask for it.
This is the part most teams skip, and it is the part that decides whether the system holds up. Routing, retries, escalation, and context assembly are operational concerns, not prompt concerns.
Company Brain
Your knowledge, grounded in your values and current goals. It knows what stays true and what expires, so agents stop answering from outdated or tribal data. It lives where your team already works, inside Claude, Slack, email, and your CRM.
It runs on open infrastructure such as Mem0, Zep and Graphiti, Letta, and Obsidian. We build it and run it, but you own it outright. If we are ever not the right partner, you take the brain with you.
AI Judge
Every output gets scored against your standards before it reaches a customer or a decision. Low-quality work gets caught and corrected, not shipped.
The judge checks grounding, policy compliance, and tone, and it verifies claims against source systems rather than model memory. Anything below the threshold routes to a person with the reason attached.
Improvement Manager
Failures become fixes. The system turns every miss into a new rule or test, so your agents get better over time instead of drifting.
Without this loop, quality decays quietly. Prompts get patched by whoever noticed the problem, nothing is tested, and six months later nobody can explain the current behavior. The improvement loop makes changes durable and reviewable.
Integration
One agent layer across the systems you already run. CRM, email, ERP, ticketing, and data warehouses. No new app for your team to adopt.
We do not replace your software. Your team keeps the tools it knows, and the agents work across them. That is what makes adoption a non-event rather than a change program.
The stack underneath
This is not a Cloudify product. It is the open-source stack, managed. Orchestration typically uses LangGraph, CrewAI, the OpenAI Agents SDK, or the Microsoft Agent Framework. The company brain uses Mem0, Zep and Graphiti, Letta, or Obsidian. Oversight uses LangSmith, Langfuse, Arize, or Braintrust.
We use the right ones for your stack, or build past them, and run the whole thing. You own every piece of it. One point of accountability, and no product only we can open.
For the sequence that produces this system, read the AI-First Method. For where it gets deployed, see the use cases or pricing.
Bring us one painful workflow. We'll make it AI-first.
Two-week AI-First Scan. A ranked opportunity map. A deployed system your team does not have to babysit.