E-commerce support & action
Where is my order, returns, delivery changes: the agent completes the transaction in the order system.
E-commerce support & action is an Aginies solution package for the Retail & E-commerce sector in the “customer interaction & experience” area. What the agents do: Intent and entity extraction: order number, product and request type understood in one turn; catalogue and policy knowledge retrieved with RAG; sizes, compatibility and return terms answered correctly. Expected outcomes: high-volume requests resolved without growing the support team; order updates, cancellations and delivery changes completed inside the conversation; product answers grounded in your knowledge sources, no fabrication. The package uses the Multi-source RAG, Supervisor · sub-agents, Session memory, REST / MCP tools capabilities of the Aginies platform and can be watched live through the Outfit stylist: a complete look by size, stock, budget and style, Where is my order? (WISMO), Returns and refunds, Product Q&A assistant scenarios in the agent library.
Support volume multiplies in season; teams answer the same ten questions while switching screens to act in the order system. Chatbots answer, but cannot cancel.
- 01Intent and entity extraction: order number, product and request type understood in one turn.
- 02Catalogue and policy knowledge retrieved with RAG; sizes, compatibility and return terms answered correctly.
- 03Tools wired to the order system change delivery details, start cancellations and issue return labels.
- 04Out-of-policy requests (high-value refunds, campaign exceptions) route to human approval.
- One dialogue agent on web, mobile and WhatsApp; order, return, delivery and product questions
- Transaction tools wired to order management, carrier and payment systems
- Catalogue and policy knowledge base; return and warranty terms with citations
- Warm hand-off to a representative with a conversation summary
- Read/write API or MCP access to order and carrier systems
- Current return, delivery and campaign policies
- A session or OTP flow that verifies the customer
Derived from the linked scenarios: the supervisors, specialist agents, models and systems that run this package.
Summed from the simulation definitions of the linked scenarios; recalculated for your scale in the discovery session.
- High-volume requests resolved without growing the support team
- Order updates, cancellations and delivery changes completed inside the conversation
- Product answers grounded in your knowledge sources, no fabrication
| First-contact resolution | +15–25 points |
| Share of conversations handed to a representative | below 35% |
| Extra representatives at seasonal peak | 40–60% lower |
Target ranges from comparable deployments; baseline and target are fixed together in the first week of the pilot.
Scenario-level approval rules plus the package’s general controls.
- Outfit stylist: a complete look by size, stock, budget and styleDiscount outside campaign rules or a bespoke price request → customer service
- Returns and refundsRefund > 2,500 or > 5 returns in 12 months → team lead approval
- packageNo refund or address change without identity verification
- packageEvery transaction in the audit trail with customer, order and agent step
- 1 · Discovery and design · 2–3 weeksThe 20 most frequent intents and transactions are chosen, identity and approval thresholds written with information security, channel and system integrations listed.
- 2 · Pilot · 4–6 weeksOne channel, a limited customer group; the test corpus runs, a human representative shadows, thresholds tuned on real traffic.
- 3 · Scale-outRemaining channels and transactions added; dashboards, SIEM forwarding and kill-switch handed over; monthly model and rule review begins.
This package’s scenarios in the agent library
Outfit stylist: a complete look by size, stock, budget and style
The customer sends a photo and a sentence; the agent builds three looks that are in stock, fit and within budget, and adds the chosen one to the cart.
Where is my order? (WISMO)
Customer asks, order and carrier events join instantly; on delay a new ETA is given and a trace opened.
Returns and refunds
Policy and history checked in seconds, label issued; the refund executes when the carrier scans the parcel.
Product Q&A assistant
Size, compatibility and spec questions answered from catalogue and return data; stock and price verified.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis