USE CASE · CUSTOMER SUPPORT

Your support AI answers
the same 200 questions all day.

Returns. Password resets. Shipping windows. Plan changes. The volume looks endless, but the questions are not. MEMStorage routes the repeats to memory and pays full inference only on the questions you have not seen yet.

See the savings Request a demo
73%
of support queries are repeats
55–70%
typical inference cost reduction
<1s
memory-hit reply latency
The problem

Support volume is repetitive.
Your bill does not know that.

Support workflows are the textbook case for memory routing. The top 50 intents drive most of the volume, and yet every ticket arrives as a new inference call.

🔁
A handful of intents drive most of the volume
"Where is my order?" "How do I reset my password?" "Can I change my plan?" Three intents will often cover 40–50% of all tickets. Your model resolves each one from scratch every single time.
73%
avg repeat rate measured across SaaS support deployments
🕐
Latency hurts CSAT
A 4–8 second model response on a question your stack has answered ten thousand times reads as a slow agent. Memory hits return in well under a second, identical answer, fraction of the cost.
~6s
avg LLM-only support response time
📞
Volume scales linearly with growth
Every new customer adds tickets. Every ticket adds inference. The cost line is permanently coupled to the user line — unless you stop paying for the answers you have already produced.
✦
The fix is a routing layer, not a new agent
You do not need to retrain, swap models, or rewrite playbooks. MEMStorage sits in front of whatever support agent you already run, and only escalates the genuinely new tickets to the model.
Why it fits support

Three ways MEMStorage
shows up in a support stack.

🧱
Drop-in router in front of your agent
Sits above your existing support AI — Intercom Fin, Ada, your in-house Claude or GPT agent, any helpdesk-native assistant. No replacement. Your routing logic, escalation rules and personas stay exactly where they are.
📚
Memory grows from your real tickets
Every confidently resolved ticket becomes a memory entry, scoped per tenant. Month 3 hits more often than month 1, because the memory layer learns the shape of your customers' questions.
🎯
Confidence thresholds you control
Tighten the bar on payment or account questions, loosen it on shipping FAQs. Route to confirm-then-answer when score is borderline. Auto-escalate complaints. All configurable per intent.
🔒
Tenant-isolated memory
Each customer's memory is siloed. Nothing crosses between organizations. Embeddings cannot be reverse-engineered to source content. Built for support orgs that handle PII and account data.
📊
CSAT-safe rollback
Every memory hit is logged with the matched intent, score, and stored answer. If a stored answer goes stale, one click invalidates and reroutes future hits to the model.
⚡
Sub-second response on repeats
A memory hit returns in 200–600ms with no model call. Your customers feel the speed; your CFO feels the savings. Both numbers are visible in the dashboard.
Estimated cost reduction

For a typical SaaS support deployment.

Modeled on a real anonymized customer running ~200K monthly support inference calls at $40K/month. Your numbers will vary; the pilot tells you the truth.

Current monthly state
$40,000
Monthly support inference calls~200,000
Avg cost per call$0.20
Repeat rate (measured)73%
Repeat compute paid for$29,200
Every repeat is a question your agent has resolved before but is paying full inference to resolve again.
With MEMStorage
$13,500
Memory hit rate (steady state)~66%
Inference paid only on novel queries$13,600
MEMStorage fee (Growth tier)$4,000
Net monthly savings$22,400
Projected annual savings$268,800
Numbers above assume the documented 75% capture rate of repetitive queries. The real pilot reports actual hit rate weekly.
Demo scenario

A morning's worth of tickets.
Routed live.

Five real-world support intents, run through the three-tier router. Memory handles the bulk, confirm validates the borderline cases, full inference only on the genuinely new ticket.

memstorage · support routing — 9:14am
MEMORY HIT
"Where is my order #45821?"Score 92% · matched stored "order status lookup" intent
0 tokens
MEMORY HIT
"How do I reset my password?"Score 96% · matched stored "password reset" intent
0 tokens
CONFIRM
"Can I downgrade and keep my custom domain?"Score 38% · sent to Claude for 20-token YES/NO confirmation
~20 tokens
MEMORY HIT
"What is your refund window?"Score 88% · matched stored "refund policy" intent
0 tokens
FULL INFERENCE
"My SSO with Okta keeps loop-redirecting after the SAML response."Score 9% · novel · escalated and stored to memory
~520 tokens
80%
Hit Rate (5 tickets)
~540
Total tokens used
~$0.04
Total spend (vs $1.00)
Get started

Pilot it on your real ticket stream.

We instrument the parallel layer, run it against 30 days of your real support volume, and report the actual hit rate and dollar delta. If the savings do not justify the fee, you pay nothing.

30-day support pilot

We mirror traffic from your existing support agent into MEMStorage, return both responses to your dashboard, and show you exactly which tickets would have been served from memory and what it would have saved.

Start the pilot → Read the support case study