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Cake for Agentic RAG

Use open-source tools to build dynamic, multi-step agent workflows that retrieve, interpret, and act on enterprise data, orchestrated on a cloud-agnostic, modular stack.

 

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Power intelligent agents with open-source, cloud-agnostic orchestration

Traditional RAG systems retrieve relevant documents and inject them into a single prompt. But with agents, you can do way more—retrieving data iteratively, reasoning across steps, and invoking tools to complete complex, goal-oriented tasks. The challenge is stitching together vector databases, chunkers, long-context models, and orchestration tools while keeping things secure and scalable.

Cake gives you a fully integrated stack for building agentic RAG systems using open-source tools. Instead of wiring together components yourself, you can orchestrate long-context LLMs, vector databases, chunkers, and routing logic with minimal boilerplate across a scalable infrastructure. Cake saves you precious setup time and ensures your agentic RAG stack stays up-to-date with the latest technologies.

Whether you’re deploying a retrieval-augmented assistant, automating multi-step decision trees, or chaining tools for reasoning and action, Cake helps you move from experimentation to production with confidence, compliance, and control.

Key benefits

  • Ship faster: Go from notebook to deployed agentic system without gluing together infrastructure.

  • Use open-source tooling: Mix and match LLMs, routers, and chunkers without vendor constraints.

  • Scale securely: Build workflows that grow with your data, teams, and compliance needs.

Common use cases

Common scenarios where teams use Cake to build agentic RAG systems:

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Intelligent support agents

Retrieve relevant context, route queries across tools, and provide multi-turn assistance grounded in real data.

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Research copilots

Use long-context models to iteratively retrieve, read, and synthesize information across multiple queries.

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Enterprise task automation

Enable agents to retrieve internal data, reason over it, and take action using custom toolchains.

Components

  • Ingestion & workflows: AirByte
  • Orchestration: Langflow, LlamaIndex
  • Models: Hugging Face models including BGE, Llama 4
  • Databases: Weaviate, Neo4j
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"Our partnership with Cake has been a clear strategic choice – we're achieving the impact of two to three technical hires with the equivalent investment of half an FTE."

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Scott Stafford
Chief Enterprise Architect at Ping

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"With Cake we are conservatively saving at least half a million dollars purely on headcount."

CEO
InsureTech Company

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"Cake powers our complex, highly scaled AI infrastructure. Their platform accelerates our model development and deployment both on-prem and in the cloud"

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Felix Baldauf-Lenschen
CEO and Founder

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