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How We Built an AI-Assisted Quoting Workflow in Salesforce: A Step-by-Step Look

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Introduction

Three hours. That is what one custom quote used to cost this manufacturer. Now it is thirty minutes. The difference is not a faster rep or a bigger team. It is a workflow we built in Salesforce, with Agentforce doing the reading and typing that used to swallow the afternoon.

And this is where the AI hype finally does something useful. Most of the value from generative AI in sales is not flashy. It is the grind work, reading documents and shuffling data between systems. McKinsey has pegged that kind of task as a big share of what AI could take off a team’s plate, and custom quoting is a textbook case.

So let me walk you through the actual build, from the first RFP to the finished comparison. No demo gloss, just the real stages and where each one lives. If you are thinking about something like this for your own quoting, this is what it takes to put one together.

The same quote before and after the workflow: the old way takes 3 hours with a rep buried in RFPs, Excel, and email; with Salesforce the quote runs as a connected flow in 30 minutes

The Workflow at a Glance

First, the whole path in one breath. A customer RFP lands in Salesforce. Agentforce reads it. A vendor document gets generated and parked in AWS S3. It goes out to vendors. Their quotes come back into Salesforce. The team compares them. The approved order rolls into QuickBooks. Six stages, one system.

StageWhat happensWhere it lives
1. IntakeThe customer RFP is uploadedSalesforce record
2. ProcessingAgentforce extracts the product requirementsSalesforce record
3. DocumentA vendor document is generated and storedAWS S3, link on the record
4. OutreachThe document goes to vendors, replies come backSalesforce
5. ComparisonVendor quotes are weighed side by sideSalesforce record
6. ApprovalThe approved order moves to accountingQuickBooks
Six-stage quoting pipeline: RFP intake, Agentforce processing, document in AWS S3, vendor outreach, comparison, and approval in QuickBooks, with Salesforce as the hub running underneath all six

Now, one at a time.

Step 1: The RFP Comes Into Salesforce

It starts with the request, so that is where we started: get the RFP into Salesforce and onto a record. From that moment, the record is the quote. The specs will hang off it. So will the generated document, the vendor replies, and the final call. Nothing important sits in an inbox or a Downloads folder anymore.

Boring? A little. But it is the hinge the whole thing swings on. Five scattered copies become one, and every later stage reads from it.

Why it matters:

  • One record, one source of truth, nothing to keep in sync
  • Anyone on the team can pick the quote up, because its whole history is right there
  • A quote cannot quietly go missing between two people

Step 2: Agentforce Reads and Structures the Requirements

Here is the stage that used to burn the most time, and where Agentforce actually earns its keep. The old way: a rep reads the RFP line by line and retypes it all into Excel. The new way: Agentforce opens the uploaded file and pulls the requirements out itself. Things like:

  • Measurements and dimensions
  • Finishes and materials
  • Quantities per item
  • Images and reference shots
  • Packaging notes

The trick is what it does with them. It does not hand back a summary someone still has to key in. It writes structured data straight onto the record, ready for the next step. So reading and data entry, the two slowest jobs in the old flow, happen in a single pass and are done.

Agentforce turns a messy RFP into structured data: an unstructured PDF, sketch, and email on the left flow through Agentforce into a clean Salesforce record with part name, dimensions, material, finish, quantity, packaging, and reference images

Why it matters:

  • It was the longest manual stage, so this is where most of the hours come back
  • Structured data, not a summary, means nothing gets retyped later
  • A messy RFP and a tidy one both come out usable, because it handles the format mess for you

Step 3: Generating the Vendor Document

With the requirements captured, the workflow builds the vendor document itself, straight from that data. Nobody rebuilds a spec sheet by hand.

Then it parks the file in AWS S3 and saves the link back on the Salesforce record. That split is on purpose. S3 holds the file, the record holds the link, and the team opens it without ever leaving Salesforce.

Why it matters:

  • Built from captured data, so every document comes out consistent, with no fresh typos
  • File in S3, link on the record, so storage scales without bloating Salesforce
  • No more digging for the latest version

Step 4: Vendor Outreach and Response Tracking

Document ready, it goes out to vendors, often suppliers overseas. This is exactly where the old process used to come apart. Everything lived in email. Follow-ups, half-answers, threads that only moved when somebody happened to open their inbox.

So we pulled that exchange into Salesforce. Vendor quotes now land back in the system instead of hiding in email chains, and each vendor's status shows on the record instead of in someone's head. The back-and-forth still happens. It just happens where you can see it.

Why it matters:

  • Every vendor's status is visible, so you know who replied and who did not
  • Nothing hinges on remembering to check an inbox
  • A stalled vendor shows up early, not when the quote is already late

Pivotal Leap Insight

Honestly, the part clients underestimate is how much of this is plumbing, not AI. Agentforce reading the RFP is the flashy stage, but the reason the workflow saves hours is that its output lands on a record the vendor step and the comparison step both read from. The AI is one link in a chain. The real win is that the stages finally share a home, so nobody is hand-carrying information between them.

Step 5: Comparing the Vendor Quotes

Quotes back in Salesforce, the team compares them in one place instead of pulling numbers out of five different emails. Price, quantity, lead time, the rest, all lined up on the record. The rep weighs them and picks.

Vendor quotes side by side on one Salesforce record: three vendors with unit price, quantity, lead time, total price, and replied or waiting status, replacing quotes scattered across separate emails

This is the stage that guards your margin. A rushed, by-hand comparison is where the wrong vendor slips through or a detail gets missed. Side by side on one screen, that risk mostly goes away, and the comparison goes back to being a judgment call, which is the one piece of this that should need a human.

Why it matters:

  • Side by side, it is much harder to miss a detail or pick wrong under pressure
  • The only manual part left is the actual decision, which is where a person belongs
  • The comparison is recorded, so you can defend the choice later instead of recalling it

Step 6: Approval and the Downstream Connection

Picking a vendor is not the finish line, because a quote turns into an order, and an order has to hit accounting. So once it is approved, the details flow into QuickBooks for invoicing and the books. No rekeying.

It runs the other way too. A customer orders through Shopify, and that order drops into Salesforce, so the team manages the rest from the same place they ran the quote. One line, from the first RFP to the final invoice, instead of a pile of tools somebody has to bridge by hand.

Why it matters:

  • Approved orders reach QuickBooks without rekeying, so accounting stops being its own chore
  • Shopify orders flow in too, so the record carries the whole order, not just the quote
  • One connected line means fewer places for an order to fall through

Why We Built It on Salesforce

The through-line across all six stages: Salesforce is the hub, everything else plugs into it. The RFP, the structured specs, the document, the vendor replies, the order, all of it lives on or links back to one record, and that is what lets each stage hand cleanly to the next. Underneath sits a short stack, each tool doing what it is best at:

  • Salesforce Sales Cloud as the central system for customers, quotes, vendors, and orders
  • Agentforce for reading RFPs and extracting product requirements
  • Shopify feeding customer orders into Salesforce
  • QuickBooks for accounting and invoice generation
  • Email integration bringing vendor communication closer to the Salesforce process
  • AWS S3 as the external document store, with links saved back on the record
Salesforce as the central hub with the connected stack around it: Agentforce for AI processing, Shopify for product and vendor data, Email for RFP intake and communication, QuickBooks for financials and accounting, and AWS S3 for document storage

Together, that is what turns a three-hour quote into a thirty-minute one. For this manufacturer, it saved close to two and a half hours a quote and freed the same team to handle two to three times the work with no extra headcount. The full breakdown is in our custom order quoting use case.

How Pivotal Leap Can Build This for You

A workflow like this is less about one feature and more about wiring the stages together around how you actually quote. That is our job. We start by learning your process, where requests land, what your vendors need, where it stalls, then build the parts that fit:

  • Salesforce configured as the central system for your quoting, vendors, and orders
  • Agentforce set up to read your RFPs and capture the specs your team quotes from
  • Document generation and storage, so nobody rebuilds spec sheets by hand
  • Vendor communication and comparison brought into Salesforce
  • Connections to the tools you already run, from Shopify to QuickBooks

If your quoting still lives across email, Excel, and separate systems, talk to Pivotal Leap about building something like this around your own process.

An AI-Assisted Quoting Workflow Is Really a Connected One

Step back and it is simple. The AI matters, but the reason this works is that every stage writes to the same record, so a quote travels from RFP to vendor to comparison to order and nobody carries it by hand. Agentforce kills the slowest manual step. The connected design kills the handoffs around it.

That is the whole story behind three hours becoming thirty minutes. Not one clever tool. A set of tools finally working from one place. If your team spends its day as the bridge between systems, this is within reach, and the six stages above are a fair map of what building it takes. If you want one like it, that is exactly the kind of thing we build at Pivotal Leap.

“The mistake people make is treating this as an AI project. It isn't. It is a workflow project that happens to use AI for one stage. The teams that get real value are the ones who connect the whole line, from the RFP to the invoice, so the information stops being retyped at every step. Agentforce is powerful, but it is the connected process around it that gives you your hours back.”

Vrushank DavdaCEO, Pivotal Leap

Want a quoting workflow like this in your own Salesforce?

Talk to Pivotal Leap about connecting Salesforce, Agentforce, and the systems you already use.

Frequently Asked Questions

How does Agentforce process an RFP?

Agentforce reads the uploaded RFP and pulls out the product requirements, things like dimensions, finishes, quantities, images, and packaging details, then writes them as structured data on the Salesforce record. That replaces the manual step of reading the document and retyping everything into a spreadsheet.

Can Salesforce automate the quoting process?

Yes. With Salesforce as the central system and Agentforce handling the reading and data entry, quoting can run from an uploaded RFP through document generation, vendor outreach, and comparison on one platform. For one manufacturer, that cut quote turnaround from about three hours to roughly thirty minutes.

Where are the generated quote documents stored?

In this workflow, generated documents sit in AWS S3, and the file link is saved back onto the related Salesforce record. S3 handles external file storage while the team still opens the document straight from Salesforce.

Does this work with Shopify and QuickBooks?

Yes. Shopify orders flow into Salesforce so the team can manage the downstream process from there, and approved orders flow into QuickBooks for accounting and invoice generation. The aim is one connected line, not separate tools someone has to bridge by hand.

How long does it take to build an AI-assisted quoting workflow in Salesforce?

It depends on your current process and how many systems you are connecting. The practical path is to map your existing quoting flow first, start with the stage costing you the most time, prove it on real quotes, and expand from there, rather than building everything at once.

PL

Pivotal Leap Editorial Team

Salesforce and Agentforce Implementation Specialists. Pivotal Leap is a Salesforce implementation and consulting partner that helps manufacturers and trading companies build connected, AI-assisted workflows across quoting, vendors, and orders.

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