AI Agent Service for Sellers
The agent proposes, a human approves, the system learns from the outcome
A working SaaS in full: six agents on a custom LLM handle a seller's reviews, listings, pricing, competitors, ads and logistics. Each agent runs in one of three modes — off, propose and wait for approval, or act within set guardrails. The point is not text generation but the feedback loop: the system records what the human approved, edited or rejected, and adapts to that particular seller.
Building the same from scratch costs on average 40–70% more — that is $21,000–25,500. And even counting the purchase price, adapting a ready product to your task comes out cheaper: you pay for the differences only, not for what is already written and proven in use. This is the studio's estimate, not a measurement: the exact figure depends on how much has to be reworked.
What is included
Six agents
- Reviews: sorts claims from ordinary feedback, drafts a reply, publishes it
- Content: product listings — titles, descriptions, attributes
- Pricing: watches demand and margin, proposes repricing
- Competitors: tracks rival listings and prices in the category
- Ads: campaign bids and budgets
- Logistics: stock, resupply, distribution across warehouses
Marketplaces
- Wildberries, Ozon, Yandex Market — the core set
- Avito — a separate add-on, with cabinets
- Uzum (Uzbekistan) and Kaspi (Kazakhstan) — regional
- Amazon — an add-on for going beyond the CIS
Self-learning
- Every agent decision is stored together with its outcome
- Approved, edited, rejected and «the human acted first» are distinguished
- An edit is worth more than an approval: it shows what exactly was off
- From that history the agent adapts to the particular seller
- Shadow mode: the agent computes but acts on nothing — quality is visible before any spend
Billing and admin
- Tariffs with different capability sets and limits
- Payment through a provider, payment history, refunds
- Promo codes: percentage, fixed discount, free days
- A referral programme with payout requests
- Admin: clients, managers with roles, payments, tickets, metrics
- Per-client accounting of model spend
Technologies
- Python 3.12
- FastAPI
- SQLAlchemy
- Alembic
- Celery
- PostgreSQL
- Redis
- React
- Vite
- TypeScript
- Docker
How it earns
- Tariff subscriptions — the main revenue, from trial to business tier
- Top-ups of generation credits beyond what the tariff includes
- Paid add-ons: individual marketplaces and extra cabinets
- A referral programme: a partner brings a seller and takes a share
- A generation-free tier — analytics and recommendations only, a cheap entry point
What it can be rebuilt into
- The core is not about marketplaces. It is a chain: a connector to an external system → the agent proposes an action → a human approves or edits → the outcome is recorded → the agent learns. Plus billing, tariffs and an admin panel. The industry is the swappable part.
- Pharmacies and distribution: the agent watches stock and expiry dates, proposes a supplier order, the buyer approves
- Real estate: the agent runs listings on portals, answers enquiries, suggests a market price, the agent-of-record edits
- Restaurants: the agent adjusts the menu and prices from sales and cost, the manager approves
- Clinics: the agent handles bookings, reminds patients, fills in the record, the administrator checks
- Logistics: the agent picks a carrier and negotiates the rate, the logistician signs off
- The connectors and the agent prompts change. The approval loops, self-learning, tariffs, payments and admin carry over as they are.
Readiness
A live service with paying customers: billing, tariffs, admin and agents are in production. The buyer needs their own marketplace keys, their own payment provider contract and their own model access key.
What we need from you
- API keys for the marketplaces it will work on
- A payment provider contract for collecting money from their own customers
- A language model access key
- A server and a domain
Prices are final, in US dollars, VAT not applicable. Payment by invoice to a legal entity.
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