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Case study

Savwinch went from manual quoting to a live sales workflow.

This project started with a manufacturing sales problem. Product complexity was high, quoting was slow, and there was no single system carrying the enquiry from first touch to quote, follow-up, and finance handoff.

30+ hrs/week

saved on quoting alone

2-4 hours to seconds

quote turnaround

5 mins

lead response benchmark

300+ products

handled in the product logic

The bottleneck

The problem was not demand. It was operational drag.

Manual quoting across 300+ products took 2-4 hours per lead. No CRM, no pipeline, no automation.

CRM lived in workarounds instead of a real operating system.
Quote follow-up depended on memory, inbox scanning, and manual admin.
Cross-system handoff between sales, finance, and fulfilment created avoidable delay.

What changed

Faster quoting, cleaner handoff, and a pipeline that could move without heroics.

30+ hours per week saved on quoting alone

Quote response time from 2-4 hours to seconds

Zero manual steps in the sales pipeline

Commercial context

During this period the operation also hit a five-minute lead response benchmark and supported 100% sales growth. The workflow rebuild gave the team the capacity to handle that lift cleanly.

Build scope

The system was not one tool. It was a connected operating layer.

Build component

CRM and dealer workflow rebuild

The first layer was a real operating system. Zoho CRM was configured around how enquiries, dealers, quotes, and follow-up actually moved through the business.

Build component

AI classification for product fit

Savwinch sold 300+ products across thousands of model and fitment variants. The classification layer narrowed the right product path in seconds instead of forcing the team through manual matching.

Build component

Automated quoting and follow-up

Once the product path was known, the system could drive quote-ready output and keep follow-up moving without relying on memory, inbox hunting, or spreadsheet clean-up.

Build component

Cross-system integration

Airwallex, Xero, WooCommerce, Google Workspace, and Zoho were connected into one workflow so the handoff between payments, finance, sales, and operations stopped breaking.

Workflow before and after

Enquiry intake

Before

Website leads, dealer requests, and direct enquiries arrived in different places with no consistent owner.

After

Lead capture landed in the CRM with context, ownership, and the next step already assigned.

Product matching

Before

Staff manually worked through 300+ products and thousands of variants to find the right fit.

After

The classification layer narrowed the correct product path in seconds and removed the slowest part of the quote process.

Quote output

Before

Quotes regularly took 2-4 hours per lead and follow-up depended on whoever remembered to chase it.

After

Quote-ready responses were prepared in seconds and follow-up logic kept the opportunity moving.

Finance and fulfilment handoff

Before

Payments, invoices, and order data lived across separate systems and needed manual reconciliation.

After

Airwallex, Xero, WooCommerce, and Zoho stayed in sync so the pipeline could move without manual re-entry.

System stack

Zoho CRMXeroAirwallexGoogle WorkspaceAI Classification

What SynergAI built

  • Custom CRM with AI product classification (300+ products, 1,000s of model variants)
  • Automated quoting, seconds instead of hours
  • Full sales pipeline: lead capture → AI classification → auto-quote → follow-up sequences → deal close → Xero invoice sync
  • Google Workspace setup (emails, dual-hosted Outlook + Google)
  • Custom Airwallex → Zoho integration (non-native, no existing pathway)

Why this page matters

This is the kind of proof page that helps both search engines and LLMs. It ties the service claim to a real workflow, a real stack, and specific operating changes instead of generic marketing copy.

FAQ

Straight answers on the Savwinch build.

Was this just an AI project?

No. The commercial win came from rebuilding the workflow end to end. CRM structure, dealer management, integrations, and AI classification all mattered. The AI layer worked because the operating system underneath it was clean.

What made the workflow difficult before the rebuild?

The quoting load was high, the product catalogue was complex, and there was no single system carrying the enquiry from first touch to quote, follow-up, and finance handoff. That is why simple plug-ins would not have solved it.

Why does this matter outside manufacturing?

Because the pattern is common. Leads arrive, somebody has to qualify them, a quote or next step has to be prepared, and follow-up gets missed when everything depends on manual admin. The Savwinch case is one version of a broader operations problem.

If your team is still pushing quotes and follow-up through manual admin, the bottleneck is probably the workflow, not the staff.

We can map the handoff, show you where the time is leaking, and tell you whether the commercial case is strong enough to build.