Experience Cloud for a connected digital storefront, Data Cloud for trusted business context and Agentforce for an AI-assisted purchase-order journey — designed to make buying easier, reduce operational friction and keep commercial decisions under human control.
The announcement
KVP has won a new deal and signed a contract with a Mumbai-based polymer manufacturer for a Salesforce Experience Cloud, Data Cloud and Agentforce implementation. The engagement brings together customer self-service through Experience Cloud, harmonised customer and product context through Data Cloud, connected order and payment processing, and Agentforce-assisted purchase-order intake and validation.
This case study announces the engagement and explains the solution. Delivery is ahead of us: the benefits below are intended outcomes, not measured results. The customer’s name and commercial terms are withheld.
The customer is an established, mid-sized, export-oriented manufacturer of silicone and other engineered polymer products. Its portfolio includes tubing, hoses, sealing components and fluid-transfer assemblies used in pharmaceutical and biopharma, food and beverage, medical and industrial applications. A multi-site manufacturing footprint and a workforce of 1,000+ employees support domestic and overseas B2B relationships.
Headquarters and customer-engagement base
Workforce supporting specialist manufacturing and customer operations
Specialist products for domestic and export customers
Background is summarised from public company information; the workforce figure is supplied by KVP. Financial figures and identifying source links are intentionally omitted.
The objective is to give buyers a secure, responsive place to discover products, build carts, place orders, make payments and access order information — while giving internal teams a structured, AI-assisted way to process emailed purchase orders.
Experience Cloud powers the storefront, Data Cloud unifies and grounds business context, and Agentforce assists the order journey. This is not a claim of Commerce Cloud deployment; each layer serves a specific operational purpose.
A branded, responsive customer storefront: catalogue categories, keyword search, product attributes, cart and minimum-order-quantity rules, guided checkout, online payments and order history. Self-registration and account onboarding connect the buyer to the business account.
Ingest and harmonise customer, contact, product, pricing, customer-to-product mappings and order data. Identity resolution links inbound sender signals to a customer account; semantic retrieval grounds product matching in maintained business data.
Provide defined product and order-related conversational assistance, plus a dedicated purchase-order intake and validation workflow. AI extracts document fields, identifies products, orchestrates commercial checks, classifies exceptions and drafts acknowledgements.
Connect the storefront to one payment gateway and one ERP for order and payment exchange. Salesforce actions, approval controls, notifications and operational dashboards connect the customer-facing journey to internal fulfilment processes.
Agentforce + Data Cloud / AI spotlight
The distinctive work is not simply an AI chat window. Data Cloud grounds Agentforce in customer, catalogue and pricing context, connecting document understanding to customer-specific commercial rules through a multi-step process.
Capture a purchase-order email and its supported PDF or image attachment. Resolve the sender to the appropriate customer account using agreed identity signals.
Use document extraction prompts to produce structured PO headers and line items. Calibrate on representative English-language customer documents, including scanned samples.
Try customer material-code cross-references, supplier SKUs and semantic description matching. Ground results in the customer's product, pricing and eligibility context rather than a generic model response.
Check product eligibility, agreed pricing, minimum quantities and defined commercial rules. Classify price variance, MOQ issues, ineligible or unidentified items, with confidence and a review summary.
Create draft orders and lines carrying validation status. Route exceptions to internal reviewers. Human approval is required before activation; unresolved exceptions are gated, with authorised override controls.
Send approved acknowledgement and validation-outcome notifications. Give operations visibility into volume, exception rates, turnaround and confidence, and connect approved order/payment events to the ERP.
Customer-specific data isolation, least-privilege access, server-side account resolution, prompt guardrails, security review and human approval are part of the proposed design. Confidence is a review signal, not a guarantee of correctness. No unattended order activation is proposed.
We will agree baselines, test sets, thresholds and numerical targets with the customer in discovery. These are proposed measurement areas; the proposal does not evidence a percentage reduction, an achieved accuracy score or a realised ROI.
Elapsed time from email receipt to review-ready draft
Reduce document handling and rekeying time
Correct line matches against a human-validated test set
Improve SKU identification across customer naming conventions
Flagged lines / processed lines; time to reviewer resolution
Identify commercial issues earlier and resolve them faster
Reviewer edits, clarifications and hand-offs per draft
Reduce repetitive work without removing approval
Elapsed time from receipt to customer notification
Give buyers earlier, clearer visibility
Active buyers and eligible orders using the storefront
Make product discovery and ordering more convenient
Successful gateway/ERP exchanges and retry/error volume
Reduce reconciliation gaps and make failures visible
We are connecting Experience Cloud storefront usability, Data Cloud customer context, Agentforce PO validation, approval and ERP hand-offs. The customer should not have to choose between a convenient digital experience and control over what becomes a committed order.
Material-code cross-references, minimum quantities, eligibility and pricing are central to the design. KVP’s role is to translate those rules into testable actions and clear exception pathways, rather than let a model guess at a valid order.
The proposal draws on KVP’s high-level experience across manufacturing, pharmaceuticals and industrial B2B Salesforce programmes. For this engagement, our plan is to test representative POs, calibrate extraction and matching, enable administrators and reviewers, and use operational evidence to guide improvement.
The proposal outlines a roughly 16-week programme across discovery and design, Experience Cloud development, Agentforce/Data Cloud and integration development, testing and UAT, and production readiness with training and stabilisation. This is a proposed delivery plan, not an announced go-live date; timing depends on agreed scope, licence provisioning, source data, API readiness and customer sign-offs.
Discovery will validate catalogue and customer mappings, PO layouts, review queues, security, licensing and credit consumption. Integration and user acceptance tests will cover the full order journey, including exceptions, failed payments, account isolation and notifications.
AI PO intake is email-based; additional EDI/API intake is not part of that scope. One payment gateway and one ERP are proposed. The portal scope is defined around the catalogue, checkout and order journey, not an unrestricted commerce suite: quote requests, invoice downloads, account statements, wishlists, returns and reordering are not included. Salesforce licences, AI usage credits and third-party charges are separate dependencies.
Our team’s perspective
“Our focus in this engagement is to make AI dependable in day-to-day operations, not simply impressive in a demonstration. Working through the proposed order journey reinforces a delivery lesson: data ownership, exception handling and user adoption must be designed together. We intend to give the customer a measurable, secure process and strengthen KVP’s own discipline in delivering human-controlled AI at scale.”
Dheeraj
VP – Delivery · KVP Business Solutions
“Engaging around this opportunity has reinforced the importance of connecting the AI conversation to the customer’s commercial priorities: easier buying, quicker order acknowledgement and less avoidable back-and-forth. The value of this partnership is not a list of Salesforce features; it is a clearer path from customer intent to a trusted order. For KVP, it is an opportunity to keep sharpening how we translate manufacturing needs into an achievable transformation roadmap.”
Shreyas
Sales Lead · KVP Business Solutions
“Designing this solution highlights why purchase-order automation needs more than document extraction. Customer material codes, catalogue descriptions, pricing and minimum quantities all influence whether a line is valid. Our plan is to ground Agentforce in the right business data and make uncertain decisions visible to a reviewer. This project will deepen our learning in combining Experience Cloud, Data Cloud and AI actions into one practical, testable customer journey.”
Akshat
Solution Consultant · KVP Business Solutions
KVP has won and signed a Salesforce Experience Cloud, Data Cloud and Agentforce implementation engagement with a Mumbai-based polymer manufacturer. This announcement describes planned scope and intended benefits, not a completed project.
The proposed email-based workflow extracts purchase-order fields, matches products against customer-specific catalogue data, validates pricing and commercial rules, classifies exceptions and creates draft orders for internal human approval.
The proposal combines Experience Cloud and Lightning Web Components for the customer storefront, Data Cloud for data ingestion and grounding, and Agentforce for conversational assistance and purchase-order extraction, matching and validation orchestration.
No. Internal reviewers approve draft orders before activation, and unresolved exceptions block activation unless an authorised override is applied.
The project aims to improve order turnaround, catalogue matching, exception resolution, customer acknowledgement and self-service adoption. Baselines, accuracy thresholds and numerical improvement targets will be agreed during discovery; no achieved results are reported.
Slide deck
Planned scope, not delivered results · kvpcorp.com
Shareable infographic
KVP · Experience Cloud + Data Cloud + Agentforce
Signed Agentforce, Data Cloud and Experience Cloud engagement for a Mumbai-based polymer manufacturer. Established, export-oriented business serving life sciences, food and industrial customers. This is a deal-win announcement, not a completed implementation.
Experience Cloud storefront with Lightning Web Components. Product discovery, cart, checkout, online payments and order history. Customer onboarding and connections to one payment gateway and one ERP.
Capture emailed purchase-order attachments and extract headers and lines. Match customer material codes and descriptions to catalogue SKUs. Check price, minimum order quantity and product eligibility.
Data Cloud grounds matching in customer, product and pricing data. Classify exceptions and present confidence with review context. Draft orders require human approval; no unattended activation.
Track PO turnaround, product-match accuracy and exception rates. Measure reviewer effort, acknowledgement speed and self-service adoption. Baseline and target values will be agreed in discovery; no results claimed.
Discovery, build, integration testing, UAT, enablement and go-live support. Calibrate AI on representative customer purchase-order samples. Deliver an auditable order journey, not automation without accountability.
Signed engagement · Intended outcomes, not achieved results · kvpcorp.com
Scope is summarised from the customer’s September 2026 Experience Cloud, Data Cloud and Agentforce implementation proposal; signed-contract status is confirmed by KVP. The confidential proposal is not published. Public background is generalised to preserve anonymity. Final implementation scope and acceptance criteria follow the agreed contract and discovery sign-off.
Start with a bounded use case, representative documents and clear approval rules — then prove value before expanding automation.