Agentic AI Meets Real-time Data with Streaming Agents

Today we are thrilled to deepen our partnership with Confluent as the announcement comes of powerful new features for Streaming Agents on Confluent Cloud and a cutting-edge Real-Time Context Engine. Unifying data processing and agentic AI workflows.

Streaming Agents enable developers to build, deploy, and orchestrate event-driven agents using fully managed Apache Flink and Apache Kafka on a unified platform. Today’s new capabilities take this further by helping teams build trustworthy agents faster and more easily, gain enhanced observability, and dramatically improve AI decision-making grounded in real-time, verifiable context.

As a Confluent Partner, we see the introduction of Streaming Agents was substantial. Trust in agentic AI responses relies heavily on bringing in the full picture of data across your business. Now with event-driven agents, data complexity and quick time to action are even more pronounced. The risks is that when agents operate on data that is stale, incomplete, or worst of all ungrounded in your specific domain data, even the most sophisticated Large Language Models (LLMs) can't deliver reliable results. This leads directly to costly brand erosion and compliance risks.

We believe the joint solution is exactly what the market demanded: a full-stack solution for building scalable multi-agent systems that are event-driven, replayable, and grounded in fresh, contextualized data. By integrating the Vectara’s AI Agent Platform with Confluent’s streaming agents, we are delivering the "motherboard" for real-time AI agents: unifying data in motion with best-in-class retrieval and generation.

The "Better Together" Value: Real-Time Context Meets Trusted AI Agents

Embedded in data streams with access to the latest, most complete, and accurate view of operational events, Confluent’s Streaming Agents effectively act as the eyes and ears of the business. Vectara’s role is to bring the motherboard and guardrails.

Vectara is the Agent Operating System for trusted enterprise AI: a unified Agentic RAG platform with built-in hybrid retrieval, orchestration, and real-time governance. Deployed on-prem (air-gapped), in your VPC, or as SaaS. When combined with Confluent's Real-Time Context Engine, the joint solution unlocks a powerful architecture:

1. Confluent Ingests and Pre-Processes Data in Real Time: Event data (transactions, logs, sensor readings) flows from any source into Confluent Cloud. Flink-powered Streaming Agents process, enrich, and transform this data instantly.
2. Vectara Indexes Real-Time Context: The processed, high-fidelity data is immediately pushed to a Vectara corpus for indexing. This ensures the RAG system is always grounded in the absolute freshest version of the truth, then actively applied to it’s Hallucination Detection to ensure the truth is held.
3. Vectara Provides Trustworthy Answers: When a Streaming Agent queries Vectara the platform delivers a high-accuracy, grounded response, complete with citations and a factual consistency score, ensuring the agent’s subsequent action is verifiable and compliant.

This architecture enables Agentic RAG Platform capabilities optimized for high-velocity, high-stakes environments.

Streaming Agents Power Trustworthy, Context-Aware Automation

Vectara and Confluent unlock agentic RAG on streaming data for the enterprise. Radically accelerating the development of AI Agents. Confluent and Vectara together offer enhanced security, governance, and explainability across all data.

● Leader in streaming data and pioneers of agentic RAG

● Focus on enterprise requirements around security, governance, and explainability

● Radically accelerates time to production for AI Assistants and Agents

High-Value Use Cases Unlocked by Real-Time RAG:

• Real-time Fraud Prevention (Financial Services): Continuously ingest transaction and user behavior data via Confluent. When a suspicious event occurs, an agent uses Vectara RAG to instantly cross-reference the customer's historical profile and internal risk policy documents to determine the correct action (e.g., approve, challenge, or block), ensuring the decision is both fast and auditable with a verifiable citation.

What’s New in the Q4’25 Release: The Agentic RAG Integration Point

The new capabilities announced today streamline the connection between Confluent’s event-driven architecture and Vectara’s Trusted AI Agent Platform:

• Embeddings for agentic RAG (Native Support): Streaming Agents now have native support for generating embeddings, which can be directly fed into Vectara for indexing. This seamless integration drastically reduces the complexity of setting up the data pipeline.
• Real-Time Context Engine (RAG Enrichment): Confluent's Context Engine serves fresh, processed streaming context to all agents. When an agent calls a RAG system, this real-time context is unified with the historical knowledge base indexed by Vectara, ensuring answers are both historically deep and instantly current.
• Observability and Debugging: Confluent's enhanced observability allows full visibility into agent actions. Combined with Vectara's Open RAG Eval and built-in hallucination scoring, developers gain an end-to-end view to reliably debug and iterate not just on code, but on RAG performance and trustworthiness.

Ready to build your first trustworthy, event-driven agent?

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