AI Workforce / Customer Support
Resolution, not deflection.
Karmaflow's AI customer support agents resolve tickets end to end — reading attachments, reasoning over prior history, and acting inside your help desk, ERP, billing, and identity tools. Containment is the wrong metric. Cost per resolved conversation is the right one, and every action is proved in an audit trail your operators can read.
Closes the ticket
- Answers from a static FAQ.
- Marks the ticket resolved when the customer stops replying.
- Customer opens a new ticket two days later.
Closes the issue
- Reads attachments, prior history, and identity.
- Acts in your ERP, billing, and IAM — within policy.
- Confirms the customer's issue is gone before closing.
The economics
Price what you keep, not what you contain.
Move the sliders to your numbers. Cost per resolved conversation is the defensible unit economics buyers of AI customer support actually purchase against; deflection rate is not.
Assumptions: agent cost per resolved conversation is held at $0.65 across volume tiers. Your actual number depends on ticket-type mix and tool-call density. See full pricing, or request the live calculator in our first call.
Anatomy of a resolution
One ticket, end to end, with the receipts.
A real customer reported their espresso machine was leaking. Here is the support conversation, alongside the exact tool calls the AI agent made in your help desk and ERP while it talked.
Identified the fault from the customer's photo and video frames.
vision.classify_fault(media=[...])
→ { fault: "VALVE_SEAL_BROKEN", confidence: 0.992 }Pulled the serial from the order history and checked coverage.
warranty.lookup(serial="K9F-220-A7…")
→ { status: "ACTIVE", expires: "2027-08-14" }Filed the replacement kit under the warranty policy, no payment step.
erp.create_order(
sku="KF-VALVE-002",
customer_id=84122,
warranty_ref="W-44910"
) → "KF-992"Closed the resolution timer once the customer confirmed.
sla.stop_timer(ticket="KF-19432", outcome="RESOLVED")What it touches in your stack
By ticket type, not by logo soup.
Help-desk integrations only matter once you can name the work they do. Here are the support ticket types Karmaflow agents resolve today and the tools they act in for each — see the full integration catalog for the complete list.
Governance
Your policy. Compiled, audited, enforced.
Your operators write policy in plain English. We compile it into the runtime constraints the AI agent honors at each tool call — see how enterprise security wraps the same controls across the platform.
Policy · refunds.md
Refunds under $2,500 are auto-issued when the customer's warranty is active and there is no chargeback in the last 90 days. Refunds between $2,500 and $10,000 require a one-line justification from a Tier 2 lead before disbursal. Above $10,000, finance approval is required.
Compiled constraints (runtime)
- guard
refunds.amount < 2_500 AND warranty.active AND chargebacks_90d == 0→ auto - route
2_500 ≤ amount < 10_000→ tier-2-queue with prefilled justification draft - route
amount ≥ 10_000→ finance-approval - auditevery disbursal signed with the rule version that authorized it
When it escalates
The handoff your humans actually want.
Escalation is not a transfer — it is a packet. Here is what your specialist sees the moment a ticket arrives in their queue.
- Summary
- Customer reports a duplicate $4,210 charge from a B2B subscription. Stripe shows two captures within 90 seconds; the second has a different idempotency key.
- Recommended action
- Refund the duplicate capture; open a follow-up to investigate the idempotency-key drift.
- Why escalated
- Amount above auto-refund threshold; potential payment-system bug, not just a single ticket.
- Customer
- Acme Industries · Enterprise · 14 prior tickets, last 30 days CSAT 4.8/5
- Sentiment trajectory
- Attached
- Stripe charge ledger · idempotency-key diff · prior duplicate-capture incident from 2026-02
Quality & trust
Claims with the method attached.
Three measured outcomes from in-production AI customer support deployments. Each comes with its measurement protocol so you can judge the result, not just read it. For the longer-form argument, see Deflection is dead — resolution is the future.
Autonomous resolution
Roughly four in five tickets are resolved end to end by the agent — read, reasoned, acted on in your tools, and confirmed with the customer — with no human touch in the loop.
Method: production tickets across deployed accounts; resolution defined as customer-confirmed and no follow-up contact within seven days.
Sentiment trajectory: neutral → delighted
Sentiment trajectory measures how the agent moves the customer from where they started to where they ended. In just over a third of conversations the customer arrives neutral or frustrated and leaves delighted — the agent did not just resolve the issue, it changed how the customer feels about you.
Method: per-turn sentiment scoring, start-of-conversation vs end-of-conversation bucket transition, measured across all completed sessions.
Tool calls audited
Every external action is logged with arguments, result, and the policy clause it satisfied. Replayable and reversible.
Method: signed audit log; tamper-evident store; exportable to your SIEM.
“We've been using Karmaflow for months. The results have been astonishingly positive.”David Coffey · VP, Enterprise Solutions, CAA North & East Ontario · Read the case study
First week
What deployment actually looks like.
Days, not months. Connect and compile the policy in the first 48 hours — the rest is your testing window. Most of the timeline is the agent drafting on live tickets while your humans still send, so every disagreement becomes a policy gap caught before go-live.
Day 1
Connect
Read-only integration with your help-desk, ERP, and identity provider — same day. No agent actions yet.
Day 2
Capture policy
Your support leads write rules in plain English. We compile them into runtime constraints overnight.
Days 3–6
Shadow mode (testing)
This is most of the timeline — and it is yours. The agent drafts every response on live tickets. Humans send. Every disagreement is a policy gap caught before anything ships in your name.
Day 7
Go live
Auto-resolve the ticket types you signed off on in shadow. Everything else escalates with full context.
Talk to us
Bring us your hardest ticket type.
We'll show you exactly what the agent would do on it — tools called, policy applied, output drafted — before any contract conversation. Self-serve sign-up launches shortly; this form is the fast lane in the meantime.