What is a multi-system retail integration?

A multi-system retail integration unifies a retail or distribution operation’s three core systems — the ERP (inventory and customer master), the point-of-sale (transaction capture), and the CRM (sales and marketing) — into a single sync layer. The layer carries daily reconciliation, vendor-API spec-drift handling, and idempotent upserts. iSimplifyMe operates one in production today for Stone City, a Chicago countertop showroom and fabricator, across its ERP, Square POS, and HubSpot CRM. Roughly 2,900 B2B accounts, 1,600-plus POS orders, 26,000-plus quotes, and roughly 1,400 receipts flow into the CRM through an iSimplifyMe-built Node and TypeScript sync layer running as four scheduled jobs on AWS Lambda + EventBridge, in an AWS account Stone City owns and iSimplifyMe administers. A twice-daily inventory and purchasing dashboard runs on the same ERP data: a catalog of roughly 11,800 products, its inventory, and its purchase orders.

The setup

Stone City is a Chicago countertop showroom and fabricator, named here with the client’s agreement. It sells to trade professionals and retail walk-ins from a catalog of roughly 11,800 products, and it ran on three vendor systems that did not talk to each other: an ERP, a Square POS, and a HubSpot CRM. Sales reps were re-typing qualified leads from the CRM into the ERP to generate a quote: double entry and data drift across systems.

iSimplifyMe was engaged to unify the three systems without a rip-and-replace. The mandate: keep the existing tools, build the integration layer, operate it.

Architecture

Everything below runs in production today, apart from the row marked planned. The four scheduled sync jobs are Node and TypeScript Lambdas on EventBridge schedules in a standalone AWS account Stone City owns and iSimplifyMe administers; the twice-daily inventory and purchasing publish runs in iSimplifyMe’s own account on the same ERP data. The planned layer on top is Layer 3 retrieval observability over the sync records.

IN PRODUCTION — FOUR DAILY SYNCS + TWICE-DAILY INVENTORY PUBLISHERPinventory + customer master~11.8K products · ~2.9K B2B accountsDAILY 10:30 · 11:00 · 11:30 UTCPOS — Squaretransaction capture1,600-plus orders → dealsDAILY 10:00 UTCCRM — HubSpotsales + marketing26K-plus quotes · receipts · dealsQUOTES 11:00 · RECEIPTS 11:30 UTC⇄→⇄iSM sync layerNode + TypeScript · 4 scheduled sync jobs dailyprobe-first vendor API · idempotent upsertsRUNTIME — IN PRODUCTION SINCE JULY 2026AWS Lambda + EventBridge cron4 sync Lambdas · error + dead-man alarms per job · client-owned AWS account, iSM-administeredinventory + purchasing publish 2×/day · runs in iSimplifyMe’s own accountPLANNED — quote-status webhook · convert-to-order · Layer 3 retrieval observability

Why this is harder than it looks

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Problem 01

Vendor API spec drift

Documented field names and enum values lag the live API. iSimplifyMe uses a probe-first methodology: hit the live endpoint with a sample of live records, dump field distributions, treat the probe as the source of truth. Without it, a sync built against the published documentation produces silently wrong stage mappings that look right in dev and break against real customer data.

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Problem 02

Full-sweep timeouts

The ERP vendor’s 30-second SQL ceiling kills any full-customer sweep partway through. The fix is to chunk by sales rep and serialize the chunks. Same dataset, no timeouts.

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Problem 03

Marketing-contact tier economics

HubSpot’s marketing-contact cap makes syncing some 25,000 retail walk-ins uneconomic — the overage alone would run roughly $5,800 a month. The decision: B2B-only sync. Retail data stays in the ERP as the system of record.

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Problem 04

Incremental sync without webhooks

Daily incremental polls on modified-since timestamps plus idempotent upserts keyed on the source-system ID close the loop without webhooks. The quotes pipe was built against the vendor’s staging endpoint, probed for the production URL, and flipped on its own when the cutover landed — no code change required.

What’s running in production today

PipeDirectionVolumeSchedule
POS orders→ CRM deals + line items1,600-plus orders, full historyDaily 10:00 UTC
ERP customers→ CRM companies + contacts~2,900 B2B accounts, incrementalDaily 10:30 UTC (chunked)
ERP quotes→ CRM quotes pipeline26,000-plus quotes, one deal per opportunityDaily 11:00 UTC
ERP receipts→ CRM receipts pipeline + payment rollups~1,400 receipts since January 2025Daily 11:30 UTC
ERP products, inventory, purchase orders→ internal dashboard~11,800 products · ~5,300 purchase ordersTwice daily, 12:00 + 18:00 UTC
CRM customer card→ ERP customer createone click per new accountOn demand

Four scheduled sync jobs daily plus a twice-daily inventory publish. Each carries logging, an error alarm, and a dead-man alarm that fires if a job does not run at all. Vendor spec drift is handled in the sync layer. Times are UTC; the syncs finish before the Chicago workday starts. iSimplifyMe-operated. Not handed off.

Build log

  1. Phase 0

    Audit + scope (April 2026)

    CRM audit complete. Object counts mapped: ~2,000 contacts, ~700 companies, ~880 deals, custom lifecycle stages and lead statuses, two pipelines. Custom property schema, vendor API token validation, pipeline structure documented.

  2. Phase 1a

    Read pipelines live (April 2026)

    POS-to-CRM order sync went live mid-April; ~880 historical orders backfilled. ERP customer sync went live a few days later, B2B-only and incremental, chunked by sales rep to stay under the vendor’s 30-second SQL timeout. Custom product, deal, company, and contact properties created in the CRM. Three scheduled daily jobs running: orders, customers, and the product catalog.

  3. Phase 1b

    Quotes in production (May 2026)

    ERP quotes sync code shipped May 1 against the vendor’s staging quotes endpoint. The vendor’s production quotes endpoint went live at the end of May, and the sync flipped over on its own via the probe. More than 26,000 quotes now sit in a dedicated CRM pipeline, one deal per opportunity — multiple revisions roll up into a single deal carrying the latest revision’s data. Sixteen custom deal properties added. The daily incremental run handles a dozen or so modified quotes per day in seconds.

  4. Phase 2

    Off the local Mac, onto AWS (July 2026)

    The three sync jobs then running — orders, customers, quotes — moved from local Mac LaunchAgents to AWS Lambda + EventBridge cron in a standalone AWS account Stone City owns and iSimplifyMe administers, with an error alarm and a dead-man alarm per job. The inventory publish moved to AWS in the same window, in iSimplifyMe’s own account, and the product catalog now feeds that publish rather than the CRM. The CRM card button went live on the vendor’s customer-create endpoint: a sales rep creates the ERP customer from inside HubSpot with one click. No more re-typing the customer record.

  5. Phase 3

    Receipts + purchasing (September 2026)

    A fourth sync pulls ERP receipts into their own CRM pipeline, with payment rollups on the associated companies and contacts, reconciled to the ERP to the cent. On the purchasing side, the vendor’s purchase-order endpoint feeds an internal inventory dashboard: last purchase cost per product, what is on order and from whom, refreshed twice a day.

  6. Phase 4

    Automation (planned)

    A webhook subscription on quote status change will replace polling. Convert-to-order and an invoices endpoint, as the vendor ships them, will close the lifecycle loop on payment. Automated CRM email sequences will fire off quote events. Layer 3 retrieval observability will sit on top of the sync records.

Built and operated, not delivered.

Most integration engagements end with a slide deck and a handoff to the client’s internal team.

This one is a running production system iSimplifyMe operates daily. On AWS since July 2026; four scheduled sync jobs and a twice-daily inventory publish as of September 2026. Vendor API quirks tracked in our own probe scripts. Alarms that page us, not the client.

Client-owned AWS.In production.iSM-operated.

Frequently asked questions

How is this different from a typical integration engagement?

It did not stop at a recommendation. It started with a CRM audit and shipped a production sync layer iSimplifyMe operates daily: four scheduled sync jobs, a twice-daily inventory publish, vendor spec drift handled in the sync layer, and an error alarm and a dead-man alarm on every job. iSimplifyMe built the architecture and runs it.

How often does the data sync between the ERP, POS, and CRM?

Daily, on a fixed schedule. Square orders sync to HubSpot deals at 10:00 UTC, ERP customers to HubSpot companies and contacts at 10:30, ERP quotes to the HubSpot quotes pipeline at 11:00, and ERP receipts to the receipts pipeline at 11:30 — all before the Chicago workday starts. The inventory and purchasing dashboard publishes twice daily, at 12:00 and 18:00 UTC. Every job carries an error alarm and a dead-man alarm.

Who operates the integration after it is built?

iSimplifyMe. The sync jobs run on AWS Lambda + EventBridge in an AWS account Stone City owns and iSimplifyMe administers; the inventory and purchasing publish runs in iSimplifyMe’s own account. The sync logs, the vendor API probes, and the alarms all land on iSM-monitored channels. The client does not need an internal data engineering team to keep it running.

How does Layer 3 retrieval observability fit into a retail integration?

It is the planned next layer. Once built, every record flowing through the sync layer would become retrievable through the same Layer 3 retrieval interface behind iSimplifyMe’s regulated-industry concierges. Operations could then ask “show me every B2B account with no quote activity in 30 days” and get an answer that cites the underlying records.

What if the vendor’s API does not support what you need?

Usually not all of it. Vendor APIs drift from their documentation, cover part of the surface, or lack an endpoint outright. iSimplifyMe treats the published spec as a starting point and probes the live API first, then files follow-up notes back to the vendor with reproducible evidence. Timeouts and rate limits are handled at the application layer, and when an endpoint is genuinely missing the build is phased: what is already exposed ships first, and the rest lights up as the vendor ships it.

How long until the first pipelines run in production?

Roughly 2–3 weeks for the CRM audit plus the first read pipelines — POS orders into CRM deals, ERP customers into CRM companies and contacts — running daily in production. Quote ingestion followed in May: the sync was built against the vendor’s staging endpoint and flipped to production on its own when the vendor’s production endpoint went live at the end of the month. Moving every job onto AWS Lambda + EventBridge took days once the account was in place. Each phase is independently useful — if the vendor takes longer on a downstream endpoint, the upstream pipes still ship.

Get Started

Discuss a multi-system integration

If you are running an ERP + POS + CRM (or similar) and your team is hand-typing data between them, we can talk through what the integration layer looks like for your stack.

Start a conversationSee the Layer 3 architecture
  • Discovery call30 min · Free · No deck — actual mechanics
  • Phase 1 timeline2–3 weeks to first pipes live in production
  • iSM-operatedDeploys, monitoring, alarms, vendor follow-ups — all on us