From inquiry to reviewed quote: how to respond faster without losing control

At 8:17 in the morning, an inquiry arrives on the WhatsApp account of a distributor in Panama City: "We need 120 boxes of nitrile gloves, delivery in David. What price can you offer us?" Quote automation for distributors can turn that conversation into a reviewed quotation in just a few minutes, as long as AI prepares the work and the team retains control over prices, exceptions, and approvals.

The difference is not in replying with an automated message. It is in connecting the inquiry with the right customer, the current catalog, available quantity, commercial terms, and the approval workflow your company already uses. This way, B2B quotations no longer depend on copying data between email, WhatsApp, ERP, and spreadsheets.

The problem is not writing a quotation

At a distributor, preparing a quotation rarely consists of writing four lines and attaching a PDF. The request may arrive by email, WhatsApp, a call summarized by a salesperson, or a form on the website. Sometimes it includes an exact reference. Sometimes it says "the blue model we bought in March."

While the team tries to interpret the order, it must also resolve operational questions:

• Does the contact belong to an active customer or a new company?
• Does the reference correspond to a current product in the ERP?
• Is the quantity available, or does it require a purchase from the supplier?
• Does the requested price comply with the list price, segment, and minimum margin?
• Does delivery to David, Colón, or Chitré change the cost or lead time?
• Does the request require approval because of a discount, credit, or volume?

Each answer may live in a different system. The ERP has inventory and base prices. The CRM stores part of the sales history. Email shows recent agreements. WhatsApp has the conversation that started it all. The result is familiar: the salesperson looks for data, operations confirms inventory, finance reviews the credit, and the customer waits.

AI for distributors makes sense when it reduces that search without hiding decisions. It can extract fields from a message, consult authorized sources, organize the information, and prepare a draft. It should not invent inventory, choose a discount outside policy, or confirm a date that no one has validated.

A simple metric helps you get started. Measure the time from receipt of a complete inquiry to the sending of an approved quotation. Also measure how many quotations come back because of an incorrect price, the wrong product, insufficient margin, or a delivery promise the team could not fulfill. Speed without accuracy only moves the problem to the next step.

The workflow worth automating

A useful workflow separates preparation from decision-making. The system handles repetitive work, while a person remains responsible for exceptions and commercial commitments.

A typical process can follow these stages:

1. Receipt of the inquiry through the authorized channel.

2. Extraction of the customer, products, quantities, destination, and requested date.

3. Validation against the ERP, CRM, and current commercial rules.

4. Preparation of a draft with sources, warnings, and outstanding fields.

5. Review by the responsible person when an exception exists.

6. Sending the approved quotation and recording the activity.

Suppose Distribuciones Istmo receives an email from Compras Médicas del Pacífico, with a delivery address in David. The message requests 120 boxes of size M nitrile gloves, a brand approved by the customer, for delivery on November 5.

The automation identifies the data and places it in a work record:

• Customer: Compras Médicas del Pacífico, RUC registered in the CRM.
• Product: nitrile glove, size M, reference GN-M-100.
• Quantity: 120 boxes of 100 units.
• Destination: David, Chiriquí.
• Requested date: November 5, 2026.
• Source channel: email received at ventas@istmo.example.

It then queries the ERP. Reference GN-M-100 is listed as active, with 180 boxes available at the Tocumen distribution center. The current price for that customer is 18.40 dollars per box. The standard lead time for David is two business days, subject to transportation coordination.

At this point, no one has approved the quotation yet. A verifiable foundation has been prepared for the team to review. That distinction matters.

What the AI should validate and what your team should decide

Automation works best when each type of decision has a clear owner. Not every field needs the same level of review. A reference number can be validated directly against the ERP. A special discount needs a sales manager.

For a first version, separate the data into four groups:

• Identification data: legal name, RUC, contact, source channel and registered address.
• Order data: reference, description, sales unit, quantity, destination and requested date.
• Commercial data: price list, currency, taxes, available credit, margin and payment terms.
• Decision data: exceptional discount, product substitution, delivery promise and required approval.

The AI can confirm that the RUC matches, that the customer is active and that the reference exists. It can also detect that the order for 120 boxes exceeds that customer’s usual purchase. That alert does not mean the order is incorrect, it means it is worth reviewing before making a promise.

The team should retain certain decisions. A salesperson can approve a quote within the authorized price list. A manager reviews discounts above 8 percent. Finance confirms a credit sale when the outstanding balance exceeds the agreed limit. Operations validates a delivery date that depends on a special route.

The rules must be written in terms the system can apply. "Large discounts need approval" leaves too much room for interpretation. "Any discount above 8 percent for customers with active credit requires review by the sales manager" makes it possible to create a verifiable condition.

The NIST AI Risk Management Framework, published in 2023, recommends defining responsibilities, documenting risks and maintaining human oversight according to the impact of each use. In a quote, that translates into something practical: recording which data came from the system, which rule was applied and who gave final approval.

A complete example with a realistic exception

Let’s return to the inquiry from Compras Médicas del Pacífico. The draft calculates 120 boxes at 18.40 dollars, for a subtotal of 2,208 dollars. The customer requests a 15 percent discount because it is comparing the offer with another supplier and promises to increase its monthly volume.

The commercial price list allows up to 5 percent for this segment without approval. The minimum margin established for GN-M-100 is 18 percent. With a 15 percent discount, the estimated margin drops to 11.5 percent. The request must leave the automated workflow.

The system does not send the customer a "yes" or a "no." It creates a task for the sales manager, Patricia Gómez, with the necessary data:

• List price: 18.40 dollars per box.
• Requested discount: 15 percent.
• Proposed price: 15.64 dollars per box.
• Estimated margin: 11.5 percent.
• History: three purchases in six months, averaging 45 boxes.
• Available inventory: 180 boxes in Tocumen.
• Additional condition: delivery in David, subject to route confirmation.

Patricia reviews the case. She confirms that the buyer has an upcoming tender, but cannot authorize the requested discount. She approves 7 percent for this purchase, with payment due in 30 days and a volume review after the first month. The new price is 17.11 dollars per box, with a subtotal of 2,053.20 dollars before taxes and transportation.

The draft is updated with Patricia’s decision. It also retains the reason for the exception, the approval date and the responsible user. The salesperson reviews the final text and sends it from the authorized channel.

The customer receives a clear quote: valid for seven days, subject to availability confirmation at the time of order, with an estimated lead time of two business days and the approved payment terms. The team keeps a record of how each figure was reached.

That is the value of connected B2B quoting. It does not eliminate commercial judgment, it gives commercial judgment better data and less mechanical work.

How to connect email, WhatsApp, and your current systems

You do not need to replace your ERP to get started. In many companies, the first version can connect incoming channels to the system that already centralizes products, customers, and prices. The integration must respect existing permissions and provide a clear path for exceptions.

The flow can work like this:

• Authorized email or WhatsApp receives the inquiry and creates an opportunity or request record.
• An extraction component identifies the fields in the message and marks the confidence level of each piece of data.
• A connection to the ERP queries customers, references, inventory, prices, and permitted terms.
• The system prepares a quote in the company's format without sending it yet.
• A responsible team member receives a task when a rule is triggered.
• Approval updates the CRM and sends the response back through the defined channel.

For WhatsApp, establish from the start which number will be connected, which conversations will be recorded, and what information can be queried. It is not advisable to make business decisions based on an isolated message if the contact is not linked to a validated customer.

For email, define which inboxes will participate. A distributor can start with cotizaciones@empresa.com and leave out personal inboxes. This reduces ownerless cases and makes it easier to measure results.

There must also be a path for when data is missing. If the customer writes "I need 50 of the usual product," the system can reply with a clarifying question or create a task for sales. It can suggest the most likely reference, but it must make clear that it is a suggestion. The user decides what gets quoted.

Systems do not have to share everything. It is better to exchange the necessary fields, with permissions and logs, than to create a broad connection that no one can review. At Altaverio, we evaluate the process, connect authorized sources, and design the flow with the controls your team needs to operate every day.

How to measure whether the process actually improved

How long does a complete quote take today? A distributor does not need to wait six months to answer that question. It can compare a two- or four-week baseline with the results of a limited pilot focused on a product family or an incoming channel.

Measure at least these variables:

• Median time from a complete inquiry to the draft.
• Median time from the draft to approval.
• Percentage of quotes sent within the agreed timeframe.
• Percentage of quotes returned due to product, price, or quantity errors.
• Number of exceptions involving discounts, credit, inventory, or delivery.
• Sales value that resulted in an order after the quote.

The median is usually more useful than the average when highly complex cases exist. If nine quotes are resolved in 20 minutes and one takes two days because of a pending approval, the average can hide both the usual experience and the specific problem.

Also define who reviews quality. For the pilot, a person from sales, one from operations, and one from finance can participate. They do not need to review every message indefinitely, but they do need to agree on a sample, review exception cases, and document what went wrong.

A reasonable pilot can use 30 to 50 real inquiries from a single product line. The team compares the result with the current process and decides whether to expand, modify, or stop the flow. The measurements must include accuracy and control. Not just the minutes saved.

Adoption depends on how the system is presented. If the salesperson has to copy the same information into three new screens, the automation will be met with resistance. If they receive a draft with sources, alerts, and a clear button to approve or return it, the change is easier to adopt.

What you can do this week

Start by observing a family of repetitive inquiries. It could be medical supplies, spare parts, cleaning products, or hotel supplies. Choose a category with a stable catalog, known pricing rules, and enough volume to learn from. This is also useful because it almost always reveals which part of the process no one has ever documented.

Gather ten recent inquiries and mark where each one stopped. Was the RUC missing? Did the product have an ambiguous reference? Was the inventory out of date? Did the discount require authorization? Did someone promise a delivery without confirming transportation?

Then document the current flow on one page. Include the systems, responsible parties, approximate times, and decisions that require approval. Do not try to automate every variation from the start. A limited process with real data produces more learning than a huge design without users.

The next step could be a free introductory conversation about a recurring process. At Altaverio, we can review how your inquiries come in, what information lives in your ERP or CRM, and where it makes sense to keep human review. If the case warrants it, the flow assessment can include a process map, an observed baseline, an access and data review, available native functions, a business case, and an implementation recommendation.

Let's talk about your process.

FAQ

Can AI send quotes to customers automatically?

It can prepare the draft and send it automatically only when the rules allow it and your company has decided that the case does not require review. For discounts, substitutions, credit, uncertain inventory, or special dates, the flow must stop and request approval.

What systems does a distributor need to automate quotations?

A usable ERP, CRM, or accounting system is usually enough to get started, as long as it contains reliable customer, product, and pricing data. The workflow can connect with email, authorized WhatsApp, and other channels through integrations with defined permissions.

How can you prevent AI from making up prices or availability?

The quotation must consult authorized sources and show where the data used came from. If the system cannot find a reference, a current price, or confirmed availability, it must mark the case as incomplete and send it for review, rather than filling in the field on its own.

How long does a quotation automation pilot take?

It depends on data quality, access, and the complexity of the rules. A pilot limited to one workflow, one product family, and one channel makes it possible to define representative cases, reviewers, and quality measures before expanding the scope.

What must a team member approve?

Your company should decide this based on commercial risk. In general, it is advisable to review discounts outside policy, product changes, credit terms, nonstandard delivery promises, and any case in which the system has incomplete data.