ERPNext AI Repricing Engine

Key Features

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

`Marketplace Listing` DocType linking each ERPNext `Item` to its channel SKU/ASIN and active strategy

Full audit trail — every change writes a `Repricing Run` with old price, new price, winning rule, competitor context, and reason

Whitelisted REST methods (`@frappe.whitelist()`) to trigger a reprice, read the current target, or pull run history from external systems

`doc_events` hooks that re-evaluate floors immediately when landed cost, `Item Price`, or a strategy changes

Client Scripts adding one-click Reprice Now and live competitor context directly on the Listing form

Role Profiles and DocType-level permissions restricting margin-floor edits and autonomous mode to authorized users

Reprice throttling and per-channel rate-limit handling with retry/backoff so marketplace API caps don't drop updates

Kanban/report views and a Repricing dashboard for buy-box win rate, price-change volume, and margin-at-risk, built on Frappe reports

Compatible with Frappe/ERPNext v15 and v16, packaged as a standard installable app for your bench

Built to order, done for you

No DIY setup — a working app, built, installed and supported by ECOSIRE.

You order

Start with a one-time build price. We scope it with you at kickoff.

We build & install

ECOSIRE builds, configures and installs it on your ERPNext.

Go live + support

You go live in about 2–4 weeks, with a post-launch support window.

About this Product

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.

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.

What you get

Installable Frappe app source code built for your Frappe/ERPNext version (v15 or v16), matched to your bench

Installation and configuration on your environment — DocTypes, scheduler events, role profiles, and channel credentials wired in

Technical documentation: DocType schema, hooks.py events, whitelisted API methods, and strategy/guardrail configuration reference

End-user guide plus a live training session for your pricing and operations team

UAT on a staging site with a signed-off test plan and a documented rollback plan before production cutover

Post-go-live support window for bug fixes and adjustments after launch

Full git repository handover — the app is yours to run, extend, or transfer

Configured starter repricing strategies and margin-floor logic seeded from your real catalog and channels

Who this is for

Amazon/Walmart buy-box seller on ERPNext

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.

Multi-channel eCommerce operations manager

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.

Margin-focused finance or pricing lead

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.

ERP/systems owner or Frappe administrator

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.

How ERPNext AI Repricing Engine Compares

Criterion	ECOSIRE	Custom Build	Competitor
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

Frequently Asked Questions about ERPNext AI Repricing Engine

Is this an existing app I can download and install instantly?

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.

How long does delivery take?

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.

How does the AI pricing work, and can it price below my cost?

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.

Which marketplaces and ERPNext versions are supported?

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.

What about support and updates after go-live?

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.

How does it integrate with the rest of ERPNext?

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.

Can we control who is allowed to change floors or turn on autonomous repricing?

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.