Before every AI response, MEMStorage determines the safest, most efficient execution path. Instead of immediately invoking a model, it evaluates the request against your business policies — and only spends compute when it should.
Execution paths evaluated before compute
Trusted Knowledge
Reuse an approved answer already validated for this merchant.
no inference · instant
Validation
Confirm freshness and policy fit before an answer is served.
lightweight check
Fresh Inference
Run the model only when a genuinely new response is required.
compute consumed
Human Review
Escalate to a person when policy requires accountable judgment.
governed exception
MEMStorage governs when models execute — not which model you use.
You define business policy. The execution layer decides the path. Every decision is logged and explainable.
Business Policy
Policy Console
Configure how your business governs AI execution. You define the rules — thresholds, escalations, and review requirements. You never write prompts.
Customer Support Policy
Applies to all customer-facing conversations · northline-apparel
● Active
Reuse trusted knowledge
Serve approved answers without invoking the model.
Validate knowledge older than
Re-check answers past this age before serving.
30 days
Confidence threshold
Minimum confidence required to reuse trusted state.
90%
Fresh inference allowed
Permit new model execution for novel requests.
YES
Escalate legal questions
Route legal and liability topics to a human.
ALWAYS
Escalate refunds above
Refund requests over this amount require approval.
$500
Escalate payment disputes
Chargebacks and disputes always reach an agent.
ALWAYS
Customer sentiment
High-risk or distressed conversations require human review.
Require human review
✓ Administrator edits business policy
✕ Administrator never edits prompts
✓ Feels like configuring IAM or security policy
Live Execution
A live customer request
Watch MEMStorage evaluate an incoming question against policy — and explain the reasoning at every step, before any compute is spent.
Incoming customer message
JR
"I'd like to return my shoes after 45 days."
channel: support chat · order #SL-40921
Execution decision
Illustrative execution trace · reasoning shown for demonstration
Governance Record
Audit Trail
Every execution generates an immutable decision record — what was decided, why, and what evidence supported it. Built for compliance and enterprise review.
Run a live execution to generate an audit record.
Execution Decision Record
#EXEC-000000
Decision
Human Review
Reason
Merchant refund policy allows returns within 30 days. Customer request (45 days) exceeds the threshold, so policy requires manual approval before any response is issued.
Confidence
96%
Inference avoided
Yes — deterministic policy conflict, no model call required
Timestamp
—
Source
Merchant Return Policy · knowledge base v12
Operations
Operations Dashboard
Real-time visibility into how your AI executes across the business — volume, path distribution, compute avoided, and confidence.
Today's requests
0
across all channels
Inference avoided
0
model calls prevented
Compute savings
0
estimated, today
Avg. latency
0
execution decision
Execution path distribution
Trusted State54%
Validation21%
Fresh Inference17%
Human Review8%
Execution confidence
0
weighted across paths
Reuse ratio
75%
trusted state + validation
Illustrative operational figures · pilot environment
Deployment
Deployment
Enterprise deployment should feel operationally simple. Connect your systems, configure policy, and go to production — no code required.
SHOPLINE Connected
Storefront and merchant account linked
✓ Connected
Knowledge Base Connected
Policies, FAQs, and approved responses indexed
✓ Connected
Orders Connected
Order, refund, and fulfillment data synced
✓ Connected
Policies Configured
Business rules and escalation thresholds set
✓ Configured
Production
Deployment status
18 min
Estimated setup time
0
Lines of code required
No code required. Enterprise deployment configured entirely through business policy.
