What is AI Product Channel?

A product intelligence layer that sits on your domain and exposes your catalog through two interfaces: an AI chat that engineers use to find parts in plain English, and a native MCP server that AI agents use to query your catalog with structured tool calls.

How large a catalog can it handle?

Proven in production across catalogs with 100k+ parts. TDK Lambda runs ~135,000 parts through AI Product Channel with real-time distributor pricing and stock in the same flow.

Why is a native MCP server important?

Engineering teams are increasingly using AI coding and design agents — Claude, Cursor, OpenAI Agents, LangChain. An MCP server lets those agents research your catalog with structured tool calls instead of scraping your PDFs. If your catalog is not AI-readable, your parts are not being considered.

How is pricing structured?

Attribution-first: you pay when we prove we drove measurable outcomes like design registration or an order. The alternative is continuing to lose engineers who land on a datasheet and disappear.

Do you support authenticated workflows?

Yes. AI Product Channel runs on your domain and can gate catalog access behind authentication when account context matters, while remaining open for discovery where that is the right trade-off.

What does deployment look like?

We ingest your catalog, datasheets, compliance and lifecycle data, and distributor feeds into a Living Profile per part. First demo on your catalog in weeks, not quarters.

AI Product Channel for OEM Suppliers

What AI Product Channel is

OEM supplier websites are evolving from page-based destinations into product intelligence layers. AI Product Channel is that new layer: built for your customers' engineers today, and built for engineering AI workflows that are already arriving.

Capability 0104

The new interaction layer for OEM supplier websites

Your page-based website still matters, but the primary interaction model is shifting toward natural language and structured tool calls. AI Product Channel sits on your domain as the interface layer for product discovery, evaluation, and next-step attribution.

What one manufacturer proved as the AI-agent shift accelerates

The largest catalogs benefit the most.

Natural-language discovery

A requirement, not a part number

Engineer

ScenarioAn engineer asked: "I need a 24V DIN-rail power supply for factory automation, at least 240W, with the right compliance status, and I need to know what is available through distribution now."

Solution

AI Product Channel returned a matching TDK Lambda part, the datasheet link, compliance status, and live distributor pricing and stock in the same interaction. No FAE call. No form.

Outcome

Under 5s to part, datasheet, and live stock

Catalog scale

135,000 parts without a product finder maze

Engineer

ScenarioInstead of drilling through filters family by family, the engineer starts with the application need and constraints in plain English.

Solution

AI Product Channel narrows the catalog to the most relevant candidates, ranked against the stated requirement, and keeps the conversation grounded in product data and documentation.

Outcome

135000

135,000-part catalog made searchable by intent

Production deployment

On the manufacturer's domain, with attribution

VP Digital

ScenarioThe interaction happens where engineers already research parts, not in a side demo or disconnected prototype.

Solution

Discovery, documentation, and distributor intelligence run on the manufacturer's domain with a verified research trail that can connect the session to sample requests, design registration, and downstream commercial outcomes.

Outcome

Production live with a verified research trail

The next design win may never touch your product finder

The same discovery problem is about to get structurally worse as engineering AI takes on more of the research workflow.

AI agents are already doing product research

Claude, Cursor, OpenAI Agents, and custom LLM pipelines are already handling comparison and early evaluation work that engineers used to do manually.

Most product discovery surfaces are unreadable to that workflow

AI agents cannot use a product finder or fill out a sample request form. If your catalog is not AI-readable, it is skipped.

Native MCP is how catalogs become usable to engineering AI

AI Product Channel exposes the same product intelligence through a native MCP server, using structured tool calls instead of scraping.

Dual-interface wins the transition

Serve your customers' engineers today through AI Chat and serve engineering AI tomorrow through the same product intelligence layer.

Who it serves

Three audiences. One product intelligence layer. Each getting what they actually need.

AI Product Channel serves your customers' engineers, AI agents, and the manufacturer through the same catalog intelligence — grounded in your Product, Application, and Customer Living Profiles.

Maya · Sr EE · just now

Need a sealed IP67 encoder, SSI output, 14-bit, under 2ms latency for a wash-down servo loop. Shortlist?

AI Assistant · grounded in Product Living Profile

Grounded inProduct Living Profile·Application Living Profile·Customer Living Profile

See AI Product Channel on your catalog.

Bring a real requirements set, part family, or distributor question. We will walk through natural-language discovery, live pricing and stock, and the native MCP server on a your catalog.

Book a live catalog demo See the full platform