GraphIQ for Revenue Operations and GTM Engineers

What is the problem with traditional enrichment data?

Most enrichment platforms rely on:

This architecture limits how teams define their ideal customer profile.

For example, NAICS code 518210 is often used to represent SaaS companies.

However, this category includes organizations as different as:

This classification lacks the precision required for modern GTM targeting.

AI agents must answer questions such as:

These questions require relationship data, not static records.

Traditional enrichment platforms store data in tables.Knowledge graphs store connections between entities.

The NAICS Code Tax describes the hidden cost of relying on outdated industry classifications to define target markets.

When companies rely on predefined industry codes, they inherit someone else’s assumptions about how the market is structured.

This reduces targeting precision.

AI agents interact with GraphIQ through the GraphIQ MCP server.

This allows agents to query the graph dynamically.

Example agent workflows include:

Your ideal customer profile is rarely defined by a single industry code.

Modern GTM targeting often requires signals such as:

Traditional datasets cannot easily represent these signals.

Here are some examples?

What subsidiaries belong to a specific company?
Which companies supply a manufacturer?
What companies are owned by a private equity firm?
What companies are similar to this organization based on capabilities and technologies?

Traditional sales funnels assume a linear process.

GraphIQ enables a diamond-shaped exploration model.

The process works as follows:

Signals may include:

This approach allows RevOps teams to move from broad discovery to precise targeting.

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