Who it is for
When this service is useful.
Technology, data, and product leaders moving a defined AI or machine-learning opportunity from exploration into a useful production system.
Problems it addresses
- AI prototypes that have not reached production
- Applications that need natural-language or machine-learning capabilities
- Models that must connect to real data and workflows
- Deployment and operational requirements around intelligent systems
What Liquid Chair does
Capability connected to implementation.
We help move AI from prototype to useful production capability by connecting models, language interfaces, retrieval patterns, application logic, and operational data to the workflows they must support.
Core capabilities
- Machine-learning systems
- Natural-language processing
- LLM and retrieval-augmented applications
- AI integration
- Model deployment and MLOps
Engagement fit
When this discipline should be close to the problem.
This work is most valuable when technical architecture and implementation choices have to be made with a clear view of the business process, users, data, constraints, and production environment.
- 01
An AI prototype works in isolation but is not integrated with production workflows
- 02
A product needs language, search, classification, ranking, or recommendation capability
- 03
Models need access to reliable data, application logic, and operational constraints
- 04
Leadership needs a practical path from AI exploration to deployable capability
What the work produces
Concrete delivery without invented guarantees.
- Intelligent application features and integrations
- Machine-learning or natural-language systems
- AI capabilities connected to existing data and software
- Deployment and operational workflows for production use
- Applied machine learning
- Natural-language systems
- LLM application patterns
- Retrieval and semantic workflows
- Deployment and evaluation
Related capabilities
The disciplines reinforce one another.
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Reliable data platforms, pipelines and architectures that make operational data usable.
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Senior engineers close to stakeholders, users, systems and data until the solution works in practice.
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Production applications, APIs and integrations built around real operating requirements.
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