AI Governance for Retail & E-commerce
When margins are counted in eight figures, AI spend has to prove it pays back. OptScale AI shows finance what it delivered, cuts the cost of every model call, keeps shopper and payment data out of public LLMs, and stops agents before a runaway loop becomes an incident
Sound Familiar?
Shopper chat, product copy and planning copilots ship fast. Then finance asks which of them paid back, security asks where customer data went, and nobody has an answer that survives a second question
You can report tokens by provider. You cannot say which AI feature, team or agent turned that money into delivered work — so budget reviews stall at "usage is up."
Peak season multiplies every call. Simple requests still go to frontier models, retries stack up, and one looping agent can burn a month of budget overnight.
Customer names, card numbers and order details land in prompts and chat transcripts that go straight to external providers — with no record it happened.
Merchandising, marketing and customer care each sign up for their own AI tools. IT has no inventory and finance sees the spend only after it lands.
Agents wired into payments, CRM or support tools can act at 3 AM, reach systems nobody approved, or repeat an action far more times than intended.
A manipulated prompt or a toxic reply from a shopper assistant becomes a screenshot. Most teams can't show which prompt produced it, or which policy should have stopped it.
How It Works
OptScale AI sits between your retail applications and every model and tool they call. Nothing about your storefront or your agents has to be rewritten.
01
Point shopper assistants, content pipelines and internal copilots at the gateway's base URL. Existing OpenAI-format calls keep working
02
Define which team may use which model, what data class may leave, and what a shopper may see — as versioned policies with rollback, scoped per team or company-wide
03
Register agents and set max cost per task, max tokens, max execution time and recursion depth, plus the MCP servers and vector stores each one may reach
04
Join spend to outcomes, watch anomalies in real time, and send finance the same numbers you use to tune routing
Where Retail Teams Use It
OptScale AI doesn't build your retail AI. It makes the shopper assistants, content pipelines and AI agents for retail operations you already run cheaper to operate, safer to expose and possible to account for
Thousands of descriptions and attributes per season: send bulk generation to cost-effective or local models and compress repetitive structured input before it is billed
Both prompts and replies scanned for jailbreak attempts, toxicity, bias and off-topic output, with block, flag or log-only modes — and PII redaction masks names and card numbers before the provider
Large refunds, after-hours writes and privilege escalations flagged in real time on tool calls routed through the OptScale MCP proxy; unapproved tools blocked by default
Per-agent cost and recursion caps with auto-stop, plus live detection of loops, drift and token bursts before they reach the invoice
Its own approved models, usage quotas and department billing, so campaign AI is visible, attributed and capped instead of hidden on a shared card
Cost per merged PR and per feature for the teams building search, checkout and apps — across gateway traffic and the coding agents they use
See What Your Retail AI Really Costs — and Delivers
Start free with up to 10 seats. Route one assistant or one agent through OptScale AI and get your first cost, guardrail and agent data on your own traffic
US Office:
1250 Borregas Avenue Sunnyvale, CA 94089, US
UK Office:
124 City Road, London, EC1V 2NX, United Kingdom
