B2B buyers ask about part numbers, replacements and branch stock. Human Element connects your ERP and product data so the assistant can answer.
B2B buyers ask for part numbers, replacements and branch stock. Those answers sit in ERP tables, supersession lists and your counter staff. Human Element turns them into live, structured data the assistant can read.
The share of B2B buying Gartner expects AI agents to handle by 2028. Agents can only buy from suppliers whose data they can read.Gartner
Our condenser fan motor is part HM-4471 and it's discontinued. What replaces it? Does the Detroit branch have one today?
The buyer has to call the branch. The order may go to a competitor who answers first.
The buyer gets the replacement, the fit caveat and branch stock in one answer, then orders.
Illustrative example.
Human Element owns the data and integration work. Webscale AI owns the platform. Both teams follow the same four steps that Webscale AI's Forward Deployed Engineers use on every deployment.
leadsprovidesFind what an agent cannot answer today and where each answer actually lives.
Audits ERP, PIM and platform data against the questions your buyers ask, including part numbers, supersessions and branch stock, then maps every gap to the system that should own it.
The AI readiness scan, the launch test question set and Commerce Context Engine connectors that read every source.
Fit, install and compliance knowledge that no system holds yet.
Interviews your counter staff, product managers and sales reps and writes their answers down as structured data your team approves.
Turns approved knowledge into grounded sources and per-agent instructions in your brand voice.
Make every attribute, variant, price and policy consistent across your systems.
Cleans and standardizes attributes across tens of thousands of SKUs with AI-assisted methods and builds or repairs the ERP connectors that keep inventory, pricing and product data in sync.
The Commerce Context Engine keeps that data live, serves the same answer on every channel and writes orders and returns back to your systems.
Test the answers before launch and keep them accurate after.
Runs the launch test with your team and sets up data governance so new SKUs arrive complete as the catalog grows.
Playground preview, conversation review, escalation rules and the merchant controls that decide what each agent knows and does.
The assistant goes live only after your team, Human Element and Webscale AI agree it answers your launch test questions correctly.
These businesses run on part numbers, supersessions and branch inventory that generic AI tools cannot see. Human Element structures and connects that data so the assistant answers like your best counter rep.
Human Element structures your product data once. The Commerce Context Engine keeps it live and serves the same facts to the assistant on your storefront and to AI agents like ChatGPT and Gemini.
Commerce Context EngineOne live, normalized context with each fact from the system that owns itThe AI Shopping Assistant sells and serves in one conversation. Buyers find parts, compare options, check an order or start a return, all answered from the Commerce Context Engine.
ChatGPT
Gemini
Perplexity
CopilotAgents in ChatGPT, Gemini, Perplexity and Copilot read structured product data through feeds and open standards such as UCP, ACP and MCP. Human Element builds MCP integrations and formats your product data to meet those requirements, so the stock and pricing an agent sees match your storefront.
Better conversion from AI assistant traffic than other traffic in March 2026, a record high.Adobe Digital Insights
Every Webscale AI Solution Partner works to the same commitments, so you know what you are getting before the first call.
Partners structure data the way the Commerce Context Engine reads it and follow the same steps as Webscale AI's engineers.
Corrections land in the system that owns the fact, so your platform stays the source of truth.
Answers are checked against the questions your team chooses before any shopper sees them.
No cross-merchant training. Your raw data stays yours, and Webscale doesn't use it to train models.
The partner owns the data and integration work. Webscale AI owns the platform and its support.
No replatforming. The engine runs alongside the platform you already have.
The Webscale AI Solutions team meets with you to outline your short-term and long-term goals.
Human Element maps your top buyer questions to the systems that hold each answer.
Connecting the Commerce Context Engine takes under a day. Your launch date depends on how much data work your catalog needs.
Both teams sign off, then the assistant goes live on your storefront.
A Solution Partner is a commerce systems integrator that prepares a merchant's data for the Webscale AI Commerce Context Engine. They audit the catalog, capture expert knowledge, normalize product data at the source system and validate answers before launch, using the same method Webscale AI's Forward Deployed Engineers use.
Human Element owns the data and integration work under the AI. That covers ERP connectors, product data cleanup across large catalogs, supersession and cross-reference data, branch inventory feeds plus MCP integration. Webscale AI provides the Commerce Context Engine, the AI Shopping Assistant and the merchant controls.
Bring one in when your product data is incomplete or spread across systems. Common signs are supersessions kept in spreadsheets, stock shown as a network total instead of by branch, attributes that differ between your ERP and storefront or product knowledge that lives with your counter staff.
Adobe Commerce, Magento, Shopify, Shopware and BigCommerce.
No. Human Element is also a Webscale enterprise hosting partner. As a Solution Partner, Human Element prepares and connects your data for Webscale AI. You can use either one without the other.
Run the free Webscale AI readiness scan on your store, then book a readiness review with Human Element. The review maps the questions your buyers ask to the systems that hold each answer.
Run the free scan to see where your product data falls short. Then book a review with Human Element to plan the fixes.
