Real-Time Context Engine
Serve fresh, trustworthy context to AI agents and applications anywhere, for smarter and more reliable outcomes.
Instant access to real-time data that matters
AI decisions reflect the current state of the business
Secure, trusted data with governance and logging
Real-Time Context Engine unifies the serving layer for real-time and historical data into a single managed service. It transforms data into structured, low-latency context for any AI agent or application to consume instantly through Model Context Protocol (MCP) – all fully managed within Confluent Cloud.
Continuously build, refine, and serve trustworthy context in real time and safely accelerate to production AI systems. Kafka and Flink stay under the hood. Simply request the data and it’s there, materialized and accessible in a fast, optimized table. This fresh representation of the business powers accurate predictions, smarter decisions, and adaptive experiences.
Unify Your Architecture for Continuous Context
Use fully managed Kafka and Flink in a unified platform to combine three critical components–streaming data capture, stream processing, and low-latency context serving via MCP–to continuously collect, process, and serve the right data for AI at the right time. Simplify and reduce operational overhead while ensuring data consistency.
Curate High-Quality Data for High-Quality AI
Curate a cleaned, structured, and derived data set from historical and real-time data that represents the current state of the business and is ready for AI to consume. Enable AI reasoning and action to be actively shaped by data at runtime by feeding context that’s optimized for size and quality, giving models exactly what they need to deliver successful outcomes.
Govern to Ensure Trusted, Secure, & Responsible AI
Leverage enterprise Stream Governance, with built‑in authentication, RBAC, private networking, and audit logging to ensure compliance and transparency as you scale AI. Ground reasoning in live traceable data instead of stale snapshots for greater accuracy and confidence.
Unlock Valuable Use Cases Across Industries
Customer support
Continuously materializes live C360 and Order360 views from streaming events like orders, payments, ticket changes, and browsing activity so AI chatbots and agents always respond with accurate, up-to-the-moment context in support interactions.
Product personalization
Ingests clickstream events, cart updates, inventory changes, and enriched product metadata to maintain live user and product profiles, enabling AI-powered personalization that reflects a customer’s current behavior and intent.
Patient scheduling & care
Join EMR updates, appointment changes, clinician availability, eligibility rules, and patient history into a live context layer so AI can provide scheduling, confirm patient readiness, and coordinate care with real-time accuracy.
Loan processing
Agents use context including latest applicant information, past loans, property and payment updates–instead of a database as their state store–to take timely action, improving customer satisfaction and operational efficiency.
Anomaly remediation
Using real-time IoT sensor data from manufacturing equipment, anomalies such as unusual vibration or temperature spikes are detected and served to an AI plant assistant to automate maintenance work orders, enabling proactive repairs before breakdowns occur.
Transportation logistics
Based on real-time location, vehicle utilization, and sentiment signals, agents automate driver and vehicle scheduling as well as capture trip data and document content to generate instant quotes through natural language.
“Thunai's AI is built on real-time data. We use Confluent to… process information as it is created. This data, like a live customer support call, user actions, or system logs, is streamed instantly. This lets our AI transcribe, understand, and act on events in the moment, not hours later.”
Ready to build reliable production AI systems?
Sign up and receive $400 to spend during your first 30 days.
- ✔ Continuously deliver trustworthy, real-time context
- ✔ Serve any AI agent or application at low latency via MCP
- ✔ Use a fully managed platform with built-in security, governance, and observability