AI agents for customer operations
Support queues are the clearest example of high-volume work with real judgment inside it. Agents handle the repeatable part and hand the rest to a person with context attached.
What breaks today
Triage is expensive. Experienced people spend their morning reading tickets to decide who should read them next.
Answers already exist, in old tickets, in docs, in someone's head. Finding them takes longer than writing a new answer badly.
Escalations lose context on every handoff. The customer repeats the story three times.
Onboarding and churn-risk follow-up are the first things dropped when the queue spikes, and they are the two that decide retention.
The agent team we deploy
Each agent does one job well. The AI Manager routes the work between them and loads the right context from your company brain on every task.
Triage agent
Classifies every incoming ticket by product area, severity, and entitlement, then routes it with a summary and the three most relevant prior resolutions attached.
Response agent
Drafts replies for known issue classes, grounded in your documented answers and the customer's actual configuration. Draft first, send after review, then auto-send only on the classes you approve.
Escalation agent
Builds the escalation packet: timeline, what was tried, account value, and the open question. Engineering gets a brief instead of a thread.
Onboarding agent
Runs the sequence, checks whether each step actually happened in the product, and nudges the accounts that stalled.
Churn-risk agent
Watches usage drops, ticket sentiment, and unanswered follow-ups, then opens a save motion with a recommended action.
What goes into the company brain
The company brain is the grounded knowledge layer the agents read from. It runs on open infrastructure that you own outright.
- Your documented answers, product behavior, and known issues, with expiry dates so old guidance stops being quoted.
- Entitlement and SLA rules by plan and account.
- Tone and policy: what can be promised, what can be refunded, what must be escalated.
- Resolved ticket history as evidence, not as a training guess.
How output gets scored
The AI Judge reviews work before it leaves the system. The Improvement Manager turns every rejection into a rule or a test.
- Every draft reply is scored for factual grounding, policy compliance, and tone before it reaches a customer.
- Commitments involving money, dates, or legal terms always route to a person.
- Scores are tracked per issue class, so you can see exactly where the system is trusted and where it is not.
How the rollout runs
- The scan measures your real handle time, deflection rate, and reopen rate as a baseline.
- Triage goes first because it is low risk and high volume.
- Response drafting goes live on the two highest-volume issue classes, then widens as scores hold.
Everything starts with the two-week AI-First Scan. From there, a single agent pilot runs $15,000 to build with $2,500 per month to operate. Full pricing is on the pricing page.
You keep your existing CRM, ERP, email, and ticketing. We build the agent layer on top of them, and we run it. See how a Cloudify agent system works for the full architecture, or browse the other workflow categories.
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.