AI Era: From Platforms to Vertical Workflows

AI Era: From Platforms to Vertical Workflows | Generated by AI

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Question: Is the trend in the AI era moving from broad To B platforms like 探迹/企查查 toward highly specific self-developed AI products and workflows?

Answer:

Yes, your direction is mostly right, but there is one nuance:

探迹 is not “unable to satisfy requirements”; rather, it is optimized for a different market.

The evolution looks more like:

Old SaaS era:

Generic platform
      |
      v
Many customers
      |
      v
Standard features


AI era:

Foundation models
      |
      v
Small team / individual developer
      |
      v
Vertical AI workflow
      |
      v
Specific business outcome

For example:

企查查 / 探迹

They solve:

“Give me enterprise information and sales intelligence.”

They need:

huge company database
data partnerships
compliance
crawling infrastructure
enterprise sales teams

This is a horizontal platform.

But AI lowers the cost of building vertical products.

Example:

Old way:

A real estate company wants:

“Find wealthy buyers interested in luxury apartments.”

They might buy:

CRM
marketing automation
data provider
analyst team

Now an AI workflow can be:

Property database
        +
Public web signals
        +
LLM reasoning
        +
Image generation
        +
CRM integration

        ↓

AI luxury property sales agent

A 3-person team can build this.

The important change:

Before AI:

Software value = features

After AI:

Software value = completed task

Example:

Old:

“Here is a CRM. You configure workflows.”

AI-native:

“Find me 100 potential buyers and prepare personalized outreach.”

The second one is much closer to a human employee.

This creates a long tail of vertical AI products:

Industry	AI workflow
Real estate	AI property sales agent
Manufacturing	AI supplier discovery agent
Legal	Contract review agent
Finance	Research analyst agent
Healthcare	Medical documentation agent
Education	Personal tutor
E-commerce	Product listing + marketing agent

However, there is a counter-force:

Large horizontal companies still matter because they own:

distribution
data
infrastructure
trust

For example:

OpenAI owns models
Microsoft owns enterprise distribution
Salesforce owns CRM ecosystem

The likely structure:

Foundation layer:
OpenAI / Anthropic / Google / DeepSeek

↓

Horizontal tools:
CRM / search / office / coding assistants

↓

Vertical AI companies:
AI real estate agent
AI insurance agent
AI factory planner

↓

Internal company agents:
custom workflows

So the opportunity is not necessarily “build another 企查查”.

It is more:

Use existing foundation models + data + domain knowledge to build a 10x more specialized agent that solves one expensive workflow.

This is similar to the early mobile era:

Before smartphones:

PC software:
Photoshop
Office
ERP

After smartphones:

Uber
TikTok
WeChat
Instagram

New platforms appeared because the new interface enabled different products.

AI agents may create a similar wave:

Old SaaS:
"Tools humans operate"

AI SaaS:
"Workers that complete tasks"

For a small AI company, vertical AI workflow products are often a more realistic attack surface than competing head-on with horizontal databases like 企查查.

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