Inkling Open AI Model: Thinking Machines Targets Specialised CX

What happened

Thinking Machines Lab has released Inkling, its first publicly available AI model, marking the company's most visible move yet after roughly eighteen months of building AI infrastructure largely away from the spotlight. The release is framed as a direct challenge to the dominant "one-size-fits-all" approach that characterises most large language models currently on the market.

Rather than competing on raw scale, Thinking Machines is positioning Inkling as a foundation for more tailored, context-specific AI — the company's central thesis being that general-purpose models sacrifice too much precision in pursuit of breadth. Inkling is open, meaning developers and organisations can access and adapt it, which signals that Thinking Machines is courting builders who want to customise AI behaviour for specific domains rather than deploy an off-the-shelf solution.

Why it matters

For customer experience practitioners and service designers, the "one-size-fits-all" critique lands in a very familiar place. Generic AI deployments in customer service — chatbots that answer every query with the same tone, the same logic, the same failure modes — are already a well-documented source of customer frustration. The behavioural economics principle at work is straightforward: customers do not experience averages. They experience their specific interaction, in their specific context, with their specific emotional state. A model optimised for the median user is, by definition, suboptimal for almost everyone.

The open nature of Inkling matters here too. Organisations that can fine-tune a model on their own customer data, brand voice and service protocols stand to close the gap between what AI promises and what customers actually feel. If Thinking Machines' bet proves correct, the competitive advantage in AI-powered CX will shift from which model a company uses to how well it has been shaped around a specific customer relationship.

The Renascence take

Most of the conversation around Inkling's launch will focus on the technical merits of open versus closed models, or on Thinking Machines as a competitive threat to incumbent AI providers. That misses the more consequential question for operators: not whether to use a specialised model, but whether their organisation has the customer insight necessary to make specialisation meaningful.

An open, customisable model is only as good as the understanding of customers that goes into shaping it. Businesses that rush to fine-tune AI on thin, poorly structured customer data will simply industrialise their existing blind spots at greater speed. The real discipline here is upstream — investing in genuine customer understanding, journey mapping and behavioural data before touching the model. Thinking Machines is handing operators a sharper tool; the question is whether they know what they are trying to carve.