LangChain Semantic Layer with Cube

How Cube and LangChain work together

With Cube’s semantic layer and LangChain, you can deliver AI- and LLM-powered data experiences that are based on context, consistent metrics, secured data, and snappy response times. Give users trusted insights through an seamless user experience with Cube and LangChain.

Power your data applications with LangChain and Cube

Headless = Customized

Decoupling BI from your front-end means orchestrating data modeling, access control, and caching once—while building presentation layers for any use case.

Easily tailor your
user experience.

Security + Governance

Reconfiguring data access control for every data app in your stack opens the door to inconsistencies and gaps. Centralize permissions upstream for uniform security.

Maintain ubiquitious
access control.

Performance + Reliability

Redundantly and directly querying your data source results in latency and unnecessary costs. Cube’s caching layer, pre-aggregations, and query queuing fix that.

Skip latency;
expect speed.

Additional information on using Cube with LangChain

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Introducing the LangChain integration

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See Cube in action

How Relata built completely native embedded analytics that runs 85% faster.

Read the Case Study

How RamSoft built its users native embedded analytics—in two weeks.

Read the Case Study

Cube helped us reduce response times 100x and increase the amount of information we could display on our customer-facing dashboards.

Thomas Ankcorn

Technical Lead at NearSt

With Cube, we’ve been able to speed up time to release a new data model to production by 5x and decrease analytics downtime by 90%.

Alessandro Lollo

Senior Data Engineer at Cloud Academy

We can develop and ship analytics products without dealing with any net new infrastructure development going forward. Our efforts are focused on what matters: the data and the UI.