SOLUTION · RETAIL & COMMERCE
Retail & Commerce: From Merchandising Ops to a Customer-Facing Copilot
Batch product-content generation, customer-service automation, and demand forecasting, wired into the e-commerce and channel systems you already run. Our FDE engineers embed for weeks and ship to production; exceptions always escalate to a human, and brand voice and claim accuracy stay under your control.
The bottleneck for retail teams isn't tooling — it's scale
The pain is concrete. Launching a catalog means writing thousands of titles, selling points, spec sheets, and localized translations — and you're always behind before peak season. During big sales events, support drowns in the same handful of questions and both speed and quality slip. Meanwhile merchandising and marketing each read their own reports, and demand forecasting comes down to gut feel and a spreadsheet. Generic AI tools can write a pretty sentence, but they won't match your brand voice, they over-promise on product claims, and they don't plug into your OMS, PIM, or support ticketing.
Tenten AI is an AI-native product studio — an FDE company. We don't hand you software to figure out alone. We embed engineers inside your team, connect your product data, brand style guide, returns policy, and historical support logs, then build a working pipeline on RAG and the model you choose — Anthropic, OpenAI, or self-hosted. Product copy is generated in batches behind a human review gate; the support Copilot answers what it can and auto-escalates what it can't; demand forecasts write straight back into your replenishment and scheduling systems.
We ship in weeks, not quarters. The first production-ready MVP typically lands in your live environment within a few weeks, running inside your VPC with no data leaving your perimeter. We solve your single most painful workflow first, prove the ROI, then expand across channels and categories.
Capabilities
01
Batch product-content generation with brand-voice locking
Feed in product attributes and images, and the system generates titles, selling points, long descriptions, SEO copy, and localized versions in batches. Your style guide is enforced as a system rule, and spec claims are checked against source data so nothing is exaggerated or mislabeled. Every batch lands in a human review queue and ships only once approved.
02
Customer-facing support Copilot with exception escalation
Grounded in your returns policy, order status, and product knowledge base, the Copilot answers inquiries, tracks shipments, and handles routine returns. When confidence is low — or money, refunds, or an escalating complaint are involved — it hands the case to a human agent with full context in one click, instead of forcing the AI to muddle through.
03
Omnichannel platform integration
We connect Shopify, your storefront, Amazon, Shopee, LINE, and your OMS/PIM/support ticketing so content and conversations stay consistent across channels. Adding a new channel reuses the same rules engine — no rewriting from scratch.
04
Demand forecasting and merchandising automation
We combine sales history, promo calendars, and external signals into SKU-level demand forecasts that write back into replenishment, pricing, and launch scheduling — putting buying and marketing on the same numbers.
05
Auditable content and conversation trails
Every generated description and every AI reply retains its source grounding, model version, and human-review record, so brand, legal, and support leads can trace and spot-check after the fact.
06
You control the model and the data boundary
Pick Anthropic, OpenAI, or self-hosted. Deployment runs inside your VPC and meets SOC 2 and GDPR requirements, so sensitive data never leaves your environment.
Use cases
Batch-launching thousands of SKUs before peak
Two weeks out from Singles' Day or Black Friday, generate titles, selling points, spec tables, and three-language versions for 2,000 incoming SKUs at once. The copy team reviews instead of writing from zero, compressing launch timelines from weeks to days.
Triaging support during big sales events
When order volume spikes, the Copilot handles the repetitive 'where's my package' and 'can I return this' queries, freeing human agents for payment disputes and high-value complaints — so average response time holds steady even at peak.
Keeping copy consistent across channels
The same product has different length and format limits on your storefront, Amazon, and Shopee. The system generates the right version per channel rule, eliminating the spec drift and off-brand voice that come from manual copy-paste.
SKU-level replenishment forecasting
Blend three years of sales curves with this season's promo calendar to produce weekly demand forecasts per SKU, written back into the replenishment system to cut peak-season stockouts and off-season overstock.
Cross-border, multilingual launches
Entering Japan or Southeast Asia, generate localized Japanese, English, and SEA-language copy from your Traditional Chinese master records — and adjust claim wording to each market's regulations.
Delivery cadence
WEEK 1
Scope and connect data
Engineers embed, scope the most painful workflow, and connect product data, brand style guide, support logs, and channel systems — confirming data boundaries and compliance scope upfront.
WEEK 2–3
MVP in production
We build the first working pipeline — usually batch product copy or the support Copilot — running inside your VPC, with human review and exception-escalation gates in place.
WEEK 4–6
Validate and tune
Validate accuracy and ROI against real traffic, tune the rules engine and confidence thresholds on feedback from brand and support leads, and stand up the audit trail.
WEEK 6+
Scale out
Extend the proven workflow to other channels, categories, and markets, and kick off the next pipeline — such as demand forecasting.
2–6 weeks
First workflow live
100%
Exceptions escalate to humans
VPC
Deployed in your environment
FAQ
Will AI-generated copy actually hold our brand voice?
Yes. We feed your style guide, wording preferences, and existing high-quality copy into the system as generation rules, rather than letting a generic model improvise. Every batch routes through a human review queue where your copy team has the final say, and nothing publishes until it's approved.
How do you keep specs and product claims from being wrong or exaggerated?
Spec data — dimensions, ingredients, compatibility — is force-checked against source records, with no room for the model to guess. Marketing claim language runs against allow-lists and block-lists by category and regulation. Every description retains its source grounding, so brand and legal can spot-check at any time.
Can the system handle peak-season traffic spikes?
It can. Both batch generation and the support Copilot are built for peak load and scale with demand inside your cloud environment. On the support side, the exception-escalation mechanism ensures that even when AI capacity is stretched, payment disputes and high-value complaints get human priority — so quality doesn't collapse.
Can you integrate with our existing e-commerce and support stack?
Yes. We connect Shopify, Amazon, Shopee, LINE, and your OMS, PIM, and support ticketing. Adding a new channel reuses the same rules engine, so you're not rewriting the integration for every platform.
Is our customer and order data secure?
Deployment runs inside your VPC, sensitive data never leaves your environment, and it meets SOC 2 and GDPR requirements. You pick the model — Anthropic, OpenAI, or self-hosted — and you set the data boundary. We never use your data for training.
Why an embedded FDE instead of buying SaaS?
Retail workflows are highly customized, and generic SaaS won't plug into your brand rules and back-office systems. Our engineers embed, solve one painful workflow and prove ROI first, ship a production-ready result in weeks, then scale out — far faster than figuring out a tool on your own.
A new era of
AI-native products
Ship your first AI use case in weeks, not quarters.