Introducing QBricks: An enterprise accelerator for AI agent development, a Built on Databricks solution

One of the key 2026 priorities for enterprise leaders is ensuring scalable, governed AI that delivers measurable ROI and sustained business impact. However, building such production-level capabilities remains complex.

In practice, AI initiatives fail—or stall at the pilot stage – not because of deficiencies in the core models or the logic behind them, but due to the surrounding production ecosystem. This is because every AI project has two essential components: the business dimension, focused on value creation and return, and the technical dimension, focused on the infrastructure and operational foundations required to scale. It is within this technical component that capabilities such as memory management, guardrails, evaluation, observability, deployment, security, governance, and cost control ultimately determine whether AI systems can scale reliably and sustainably.

Launching QBricks, a Built on Databricks solution

To address this challenge, Qubika is proud to announce the public launch of QBricks, a Built on Databricks solution designed to accelerate and manage the end-to-end lifecycle of enterprise AI agents.

QBricks is a comprehensive enterprise accelerator that streamlines how organizations design, develop, evaluate, deploy, and operate intelligent agents at scale. Crucially it provides managers and leaders visibility into what is actually happening with their AI agents – how many agents are running, how much they cost, where they fail, and whether they’re delivering value.

Already in active use across multiple Qubika clients, QBricks provides a centralized, production-ready platform that emphasizes scalability, observability, and compliance from day one.

Architectural principles and key benefits of QBricks

QBricks is purpose-built for enterprise environments, combining flexibility with robust governance.

• Secure and compliant by design. QBricks runs natively on the Databricks Data Intelligence Platform, ensuring alignment with industry standards including SOC 2, GDPR, and ISO 27001.

• Enterprise-grade data privacy. All data remains encrypted, access-controlled, and fully contained within the customer’s own cloud or preferred infrastructure. This ensures data sovereignty, minimizes external dependencies, and reduces risk associated with third-party data movement.

• Seamless cloud and databricks integration. QBricks integrates directly with Databricks and supports deployment across any enterprise cloud or infrastructure configuration.

• Reusable, standalone code with no vendor lock-in. Agents built with QBricks are fully portable. They function independently of Qubika and can be executed on any mainstream agent orchestrator, giving organizations complete ownership and long-term flexibility.

QBricks standardizes the design, deployment, and monitoring of AI agents

QBricks enables enterprises to scale AI safely and predictably by standardizing four critical layers of the AI stack.

• Layer 1: Management and Governance gives leaders real-time visibility into what AI is doing across the organization – what agents exist, how they perform, where they fail, and what they cost. This transparency is essential for trust, accountability, and budget control, and prevents AI initiatives from becoming opaque experiments that stall adoption.
• Layer 2: Deployment and Runtime ensures AI agents can be reliably operated at scale, with controlled rollouts, versioning, rollbacks, and multi-environment deployments. This allows organizations to move beyond pilots and run agents without operational risk.
• Layer 3: Agent Design and Composition accelerates delivery by providing reusable patterns and building blocks, reducing development time, improving consistency across teams, and lowering maintenance costs – so teams focus on business outcomes, not rebuilding the same AI infrastructure every time.
• Layer 4: Evaluation, Observability, and Security ensures AI systems are measurable, reliable, and compliant from day one. Organizations can continuously track accuracy, performance, and cost, enforce access controls and guardrails, and quickly detect issues before they impact users. Together, these layers turn AI from isolated tools into trusted, AI-native workflows that deliver sustained business value.

Built on Databricks for scalable AI innovation

QBricks is a certified “Built on Databricks” solution, leveraging the power of the Databricks Data Intelligence Platform, which enables more than 20,000 organizations worldwide to unlock value from their data for analytics, AI applications, and intelligent agents.

Architecturally, QBricks integrates with:

• Databricks Lakebase for unified data access
• Databricks Vector Search for low-latency semantic retrieval
• GraphFrames for graph-based reasoning and relationship modeling

This architecture enables seamless integration with enterprise data sources, large language models (LLMs), and downstream systems while preserving a single operational control plane.

For those organizations not using Databricks, QBricks can also be deployed in the cloud of choice (AWS, Azure, GCP) or using a hosted environment from Qubika. It is built on LangGraph, the market leader in agent frameworks and the gold standard for building structured, reliable agent systems.

Core capabilities built for production

QBricks delivers a powerful, production-ready ecosystem of tools and capabilities:

• Pre-built agents and reusable workflow templates
• Visual agent workflow builder
• Comprehensive evaluation framework
• End-to-end observability dashboard
• Production-ready agent ecosystem

Together, these capabilities enable teams to move from experimental agents to governed, observable production systems.

QBricks’ curated library of agent templates

At the core of QBricks is a curated library of agent templates that address common enterprise use cases, including:

• Retrieval-Augmented Generation (RAG)
• Translation and transformation pipelines
• API-driven and event-based automations

These templates enable teams to move from concept to deployment significantly faster, while adhering to enterprise standards for scalability and governance.

An agent template in action: RAG agent template overview

As an example of one of the many templates that QBricks offers, we’ll take a look now at the RAG agent template. The template encapsulates a proven, end-to-end retrieval and generation workflow optimized for enterprise knowledge access, including:

1. Interpreting and understanding the intent of a user query
2. Extracting key concepts from the request
3. Resolving concepts and relationships using a graph database (PostgreSQL with the AGE extension)
4. Retrieving relevant context via vector search
5. Re-ranking results based on relevance to the original query
6. Generating a grounded response with source attribution

The RAG agent template is built on top of LightRAG, which provides a unified interface for document ingestion, parsing, embedding, and context retrieval. Internally, LightRAG orchestrates multiple components to deliver high-quality, context-aware responses:

• A vector database for embedding storage and similarity search
• A graph database for managing concepts and relationships
• A reranking service to refine and filter retrieved context
• Large Language Model (LLM) invocation and response generation
• Query caching for improved performance and efficiency

LightRAG manages the full RAG orchestration flow, including key term extraction, vector and knowledge graph searches, reranking, and LLM execution.

For users of QBricks, to include the RAG Agent in a workflow, the process is simple –  just drag and drop the rag_agent node from the left sidebar, and connect it with other workflow components such as routers, Slack integrations or chat agents. The impact of this is the enablement of rapid composition of end-to-end AI workflows with minimal effort.

Accelerating enterprise AI, responsibly

With QBricks, organizations can confidently move beyond pilots and proofs of concept, deploying AI agents that are secure, compliant, observable, and scalable. It represents Qubika’s commitment to helping enterprises realize real, measurable value from AI – faster and with less risk.

To learn more about QBricks and Qubika’s AI services and capabilities, visit https://qubika.com/agentic-factory/