The Biggest Contradiction in Industrial Vision: Customers Want Customisation, Companies Need Standardisation

The more complex the industrial scenario, the harder it is to find an off-the-shelf vision solution.
Reflective steel plate inspection, transparent part inspection, flexible material defect detection, complex assembly inspection, non-standard process inspection…
Customers are willing to pay for these scenarios, and pay quite a lot.
But many vision companies are unwilling to take them on.

Why?
Because customisation costs are too high.
The algorithm team has to tune models.
The engineering team has to modify light sources.
The mechanical team has to adjust mechanisms.
On-site debugging must be repeated.
For a single project, the contract value may be several hundred thousand, but the labour cost invested is extremely high, and it is not profitable.

This forms the biggest contradiction in the industrial vision industry:

Customers need customisation, while companies need standardisation.

01Standardisation Can Solve the 80-Point Problem; the Remaining 20 Points Are Where True Value Is Created

Over the past decade, many industrial vision companies have been desperately building standard products.
Standard cameras.
Standard software.
Standard algorithm packages.
Standard solutions.
Because only standardisation enables replication.

But reality is cruel.
Truly high-value demands almost never have standard answers.
Especially in industries such as new energy, semiconductors, aerospace, and high-end equipment manufacturing.
Every factory is different.
Every production line is different.
Even different batches of products from the same factory are different.

So many enterprises have discovered:
standard products can solve the 80-point problem.

The remaining hardest 20 points are where true value is created.And these 20 points often determine whether the customer pays.

02Evolving from a "Project Development Model" to a "Platform Training Model"

So how can this contradiction be resolved?
In recent years, a very interesting trend has emerged in the industry.

In the past: one project corresponded to one algorithm engineer.In the future, it may become: one industry model serving hundreds of projects.

With the development of vision large models and multimodal models, industrial vision is evolving from a "project development model" to a "platform training model."

Previously, when encountering a new scenario:
re-collect data. re-label. re-train. re-deploy.

Now more and more systems are beginning to adopt a pre-trained model + few-sample fine-tuning approach, substantially reducing algorithm development costs.

What does this mean?

It means what is most expensive in the future is no longer the algorithm.But industry knowledge.

You will notice a very interesting change:
what industrial vision companies compete on is no longer who can train YOLO.
But who better understands batteries.
who better understands PCBs.
who better understands automotive parts.
who better understands semiconductor processes.

Because algorithms are gradually becoming platformised, while industry experience is becoming increasingly valuable.

More importantly, low-code vision platforms are also maturing rapidly. Many new-generation vision systems are beginning to let quality engineers, rather than algorithm engineers, participate in model updates and defect definition.

Behind this is actually a bigger trend:

What industrial vision companies sell in the future is not algorithms, but "industry capability packages."Algorithms are just the foundation.Data is the fuel.Industry knowledge is the moat.

03The Future Will Not Move Toward Complete Standardisation, but "80% Platform + 20% Customisation"

So here is a rather counterintuitive judgment:

The future industrial vision industry will not move toward complete standardisation.But rather toward an "80% standardised platform + 20% industry customisation" model.

Standardisation is responsible for reducing costs.
Customisation is responsible for creating profits.
The algorithm team is responsible for building the capability platform.
The engineering team is responsible for solving the last mile.
Neither can be missing.

04The Higher the Level of Manufacturing Automation, the Harder the Remaining Problems

Many people think industrial vision has entered a red ocean.
But what is seen is quite the opposite.
The scenarios that are truly hard to do are actually increasing.
Because the higher the level of manufacturing automation, the harder the remaining problems.
And these hard problems are precisely the greatest incremental market for industrial vision in the next decade.

So the most valuable companies in the future may not be the ones with the strongest algorithms.
But rather those that simultaneously possess:

an algorithm team + an engineering team + an industry know-how team.

Because only by combining these three can the problems that others cannot solve be turned into solutions that can truly be delivered, implemented, and profitable.

This, perhaps, is the greatest opportunity in the next stage of the industrial vision industry.