A build-to-order Frappe app that turns ERPNext into your repricing brain — monitoring competitor prices per channel and pushing rule- and AI-driven price updates to Amazon, Walmart, and eBay while margin guardrails protect every sale. ECOSIRE scopes, builds, installs, and supports it for your catalog. Built to order by ECOSIRE for ERPNext v15, v16 — indicative price from $499.00 USD; request a quote for a scoped proposal.

A build-to-order Frappe app that turns ERPNext into your repricing brain — monitoring competitor prices per channel and pushing rule- and AI-driven price updates to Amazon, Walmart, and eBay while margin guardrails protect every sale. ECOSIRE scopes, builds, installs, and supports it for your catalog.
Aucun paiement maintenant. Ceci envoie une demande de devis à notre équipe — nous vous recontacterons par e-mail avec les tarifs et les prochaines étapes.
If you sell on Amazon, Walmart, or eBay, price is the single biggest lever on your buy-box share — and it moves by the minute. Managing that from spreadsheets or a disconnected third-party repricer means your ERPNext Item costs, landed freight, and margin targets live in one system while the actual selling price is decided in another. ERPNext core has Item Price, Price List, and Pricing Rules, but they are static: nothing watches your competitors, nothing understands the buy-box, and nothing safely pushes a new price back to the channel every few minutes without a human in the loop. That gap is where sellers either leave the buy box on the table or race to the bottom and erode margin.
Per-channel competitor price monitoring stored as `Competitor Price` records, scheduled via `scheduler_events` in `hooks.py` at a cadence you choose (minutes/hourly/daily)
Buy-box / win-price targeting rules — match, beat-by-amount, beat-by-percent, or hold-when-you-own-the-box — configured per `Repricing Strategy` DocType
Margin-floor and ceiling guardrails enforced in DocType `validate` against the item's landed cost, so no rule or AI suggestion can breach the floor
AI demand-based price suggestions from velocity, buy-box win rate, and elasticity computed over your own `Repricing Run` history
Advisory vs. autonomous mode per strategy — suggestions either queue for human approval or push automatically within guardrails
Scheduled bulk price push to channels executed as Frappe background jobs on the worker queue, so large catalogs never block the desk UI
The ERPNext AI Repricing Engine is a proper Frappe app (installable on your bench, v15 and v16 supported) that closes that gap inside ERPNext instead of alongside it. We model the domain as first-class DocTypes — a Marketplace Listing linking your Item to its per-channel SKU/ASIN, a Repricing Strategy holding your rule set (beat-lowest-by, match-buy-box, hold-if-you-own-it), a Competitor Price log capturing observed offers per channel, and a Repricing Run audit record for every price change with old price, new price, the winning rule, and the reason. Margin-floor and ceiling guardrails are enforced at the DocType validation layer, so no rule — and no AI suggestion — can ever push a price below the floor you set against the item's landed cost.
Technically, the engine runs on Frappe's own primitives. scheduler_events in hooks.py drive the polling cadence (every N minutes, hourly, daily) to pull competitor offers and recompute target prices; long pulls and bulk pushes run as background jobs on the Frappe worker queue so the UI never blocks. doc_events hooks fire on cost or strategy changes to recheck floors immediately. The AI layer takes demand signals — velocity, buy-box win rate, price elasticity across your own Repricing Run history — and produces a suggested price that the rule engine then clamps to your guardrails; suggestions can run in advisory mode (queued for approval) or fully autonomous per strategy. Every channel push goes out through the marketplace API and is written back as a Repricing Run, and whitelisted methods exposed over the Frappe REST API let your other systems trigger a reprice, read the current target, or pull the audit trail. Client Scripts add one-click "reprice now" and live competitor context on the Listing form; Role Profiles and DocType permissions keep the margin-floor and autonomous-mode controls to authorized users only.
Because this is build-to-order, we start from your real catalog and channels, not a generic template. After a short scoping call we confirm which marketplaces, which repricing rules, your margin-floor logic, and your approval workflow, then build the app against Frappe/ERPNext v15 or v16 to match your bench. You get the installable source, a UAT pass on a staging site, and a rollback plan before anything touches production. Typical delivery is 2–4 weeks from confirmed scope, and you receive the full git repository so the app is yours to run, extend, or hand to another team.
Runs a high-SKU catalog where buy-box share drives revenue and needs automated, minute-level repricing that still respects the margin floors already modeled in ERPNext — without exporting data to a separate repricer.
Owns pricing across Amazon, Walmart, and eBay and wants one place — ERPNext — to define rules, watch competitors, approve or automate changes, and audit every price move with a clear reason and old/new value.
Cares that no automated or AI-driven change ever prices below landed cost. Needs enforceable floor/ceiling guardrails, role-restricted controls over autonomous mode, and a full `Repricing Run` audit trail for review.
Responsible for the bench and integrations. Wants a clean, standard Frappe app on v15/v16 with proper DocTypes, scheduler events, whitelisted REST methods, and the git repo handed over — not a black-box add-on.
Achetez la licence sur ecosire.com et téléchargez le ZIP de l'application ERPNext AI Repricing Engine depuis le tableau de bord de votre compte.
Extrayez le ZIP dans le dossier d'applications de votre banc ou exécutez « bench get-app » avec le chemin d'accès à l'application extraite.
Exécutez `bench --site SITE_NAME install-app APP_NAME` suivi de `bench migrate` pour installer ERPNext AI Repricing Engine et appliquer son schéma.
Ouvrez les paramètres de licence ECOSIRE sur votre site et activez votre clé de licence. Nécessite les applications gratuites ecosire_connect et ecosire_license_client.
| Critère | ÉCOSIRE | Construction personnalisée | Concurrent | Odoo natif |
|---|---|---|---|---|
| Competitor monitoring | Per-channel `Competitor Price` records on a scheduler you set | Possible but you design and maintain the poller yourself | Often present but generic, not tied to your ERPNext costs | |
| Buy-box targeting rules | Match/beat/hold rules per `Repricing Strategy` DocType | Whatever you build and test from scratch | Preset rule packs, limited customization | |
| Margin-floor guardrails | Enforced in DocType `validate` against landed cost | Depends entirely on your implementation discipline | Basic min/max price, often disconnected from ERP cost | |
| AI demand-based pricing | Suggestions from your own velocity/elasticity, clamped to floors | Build and train it yourself, or skip it | Sometimes a black-box add-on, extra fee | |
| ERPNext integration | Native app — DocTypes, hooks, whitelisted REST methods | Native if you build it well; your maintenance burden | External tool, data synced back and forth | |
| Audit trail | Every change logged as a `Repricing Run` with reason | Only if you build logging in | Vendor-side history, limited export | |
| Ownership | Full git repo handover; the app is yours | You own it — and all the build effort | Licensed/subscription; you never own it | |
| Time to value | 2–4 weeks build-to-order from confirmed scope | Months of design, build, and testing | Fast signup, but generic fit and ongoing fees |
No. The ERPNext AI Repricing Engine is build-to-order. ECOSIRE scopes it to your marketplaces, catalog, and repricing rules, then builds, installs, and supports it. There is no instant self-download — the value is a Frappe app tailored to how you actually price and to your Frappe/ERPNext version.
Typical delivery is 2–4 weeks from confirmed scope. After a short scoping call we lock the channels, repricing rules, margin-floor logic, and approval workflow; the timeline runs from that sign-off. Larger catalogs or additional marketplace integrations can extend it, and we confirm the estimate in writing before we start.
The AI produces demand-based suggestions from your own velocity, buy-box win rate, and elasticity history. It never has final say on price — every suggestion is clamped by margin-floor and ceiling guardrails enforced in the DocType validation layer against landed cost. It cannot breach your floor, and you can run it in advisory (approval-required) or autonomous mode per strategy.
We build against the marketplaces you sell on — commonly Amazon, Walmart, and eBay — using each channel's official API for competitor reads and price pushes. The app is packaged for Frappe/ERPNext v15 and v16 and installed on your bench. Confirm your exact channels and version during scoping so we target them precisely.
Every build includes a post-go-live support window for bug fixes and adjustments. Because you receive the full git repository, your team can maintain and extend the app independently; ECOSIRE also offers ongoing support and enhancement engagements for new channels, rule changes, or version upgrades to future Frappe/ERPNext releases.
It runs inside ERPNext as a standard Frappe app. It reads item costs and links each `Item` to its channel listing, drives updates through `scheduler_events` and background jobs, reacts to cost/strategy changes via `doc_events`, and exposes whitelisted REST methods so external systems can trigger a reprice or pull the audit trail. No separate parallel system to reconcile.
Yes. Margin-floor edits and autonomous-mode toggles are protected by Frappe Role Profiles and DocType-level permissions, so only authorized users can change guardrails or enable automatic pushes. Every price change is logged as a `Repricing Run` with the acting user, winning rule, and reason for full accountability.
A build-to-order Frappe app that turns ERPNext into your repricing brain — monitoring competitor prices per channel and pushing rule- and AI-driven price updates to Amazon, Walmart, and eBay while margin guardrails protect every sale. ECOSIRE scopes, builds, installs, and supports it for your catalog.