Every support interaction starts with "Can you tell me your order number?" or "What was the issue you reported last week?" Your customers hate it. Your agents waste time. Memory fixes this.
Most AI support tools treat every conversation as if it's the first. A customer who's contacted you 10 times about the same billing issue gets the same generic response as a first-time visitor. The AI has no idea who they are, what they've bought, or what problems they've had before.
This creates three problems:
They have to explain their situation from scratch every time. "I already told you this last week" is the most common complaint in support tickets.
Your AI spends the first 2-3 exchanges just gathering context that should already be available. That's 40% of the conversation wasted on information retrieval.
Without history, your AI can't recognize patterns. It can't say "I notice this is the third time you've had this issue — let me escalate to engineering" or "Based on your usage, you might benefit from our Pro plan."
With MemoryStack, every customer interaction is stored and instantly retrievable. When Sarah contacts support, your AI already knows she's been a Pro customer since March, had two billing issues (both resolved), prefers email follow-ups, and is based in PST timezone.
Before your AI generates a response, it searches the customer's memory. In under 100ms, it has their complete history — purchases, tickets, preferences, everything.
Your AI doesn't just know facts — it understands context. It knows this customer prefers detailed technical explanations, or that they've been frustrated with slow responses in the past.
Every interaction is stored automatically. Your AI gets smarter with each conversation, building a richer understanding of each customer over time.
No more back-and-forth gathering basic information. Jump straight to solving the problem.
With full context, AI resolves issues that would otherwise need human intervention.
Customers notice when you remember them. Personalization drives satisfaction.
MemoryStack integrates with your existing support stack. Two API calls — one to retrieve context, one to store the interaction. Works with any AI provider.
from memorystack import MemoryStack
client = MemoryStack(api_key="your-api-key")
async def handle_ticket(customer_id: str, message: str):
# Get full customer context in one call
context = await client.search(
query=message,
user_id=customer_id,
limit=10
)
# Your AI now knows:
# - Previous issues and resolutions
# - Customer preferences
# - Account details
# - Communication history
response = await generate_response(message, context)
# Automatically stored for next time
await client.add(
content=f"Issue: {message}\nResolution: {response}",
user_id=customer_id
)
return responseStart with 1,000 free memories. No credit card required.