Generic outreach gets ignored. Your AI needs to remember what each prospect cares about, what objections they've raised, and where they are in their decision process.
You've tried AI for sales outreach. The emails are grammatically correct but feel robotic. They mention the prospect's company name but nothing specific. They get deleted without being read.
The problem isn't the AI — it's the context. Your AI doesn't know:
In your last call, Sarah mentioned she's worried about API latency, not cost. But your AI keeps sending emails about pricing because that's what the template says.
Marcus is evaluating three vendors and needs to decide by month-end. Your AI doesn't know this, so it sends a "let's schedule an intro call" email to someone who's already deep in evaluation.
Your SDR had a great conversation last week. Now the AI sends a follow-up that ignores everything discussed. The prospect thinks you don't care enough to remember.
With MemoryStack, every interaction is stored and instantly retrievable. When your AI writes a follow-up, it knows exactly what this prospect cares about, what objections they've raised, and what's been promised.
Calls, emails, LinkedIn messages, meeting notes — everything goes into memory. Your AI builds a complete picture of each prospect over time.
Before writing an email, your AI retrieves relevant context. It knows to mention the API latency concern, reference the month-end deadline, and avoid topics already covered.
When an SDR hands off to an AE, all context transfers automatically. No more "let me get up to speed" calls. The AE knows everything the SDR learned.
Personalized outreach gets responses
Relevant emails get read
Context-aware selling works
No time wasted re-learning
MemoryStack works alongside your CRM, not instead of it. Store context from Salesforce, HubSpot, or any system. Retrieve it when generating outreach.
from memorystack import MemoryStack
client = MemoryStack(api_key="your-api-key")
async def generate_followup(prospect_id: str, trigger: str):
# Get everything we know about this prospect
context = await client.search(
query=f"prospect context {trigger}",
user_id=prospect_id,
limit=15
)
# Context includes:
# - Previous conversations
# - Objections raised
# - Decision timeline
# - Stakeholders mentioned
# - Competitor comparisons
email = await generate_personalized_email(
trigger=trigger,
context=context
)
# Store this touchpoint
await client.add(
content=f"Sent follow-up: {email[:200]}...",
user_id=prospect_id,
metadata={"type": "outreach", "trigger": trigger}
)
return emailStart with 1,000 free memories. Build AI that sells like your best rep.