Coming Soon

The Agentic
Data Plane

AI that monitors, validates, and protects your data in real-time.
Fully automated.

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Platform Capabilities

Intelligent Data Operations

Deploy AI agents that learn your data patterns and automatically identify issues before they impact your business.

Anomaly Detection

Automatically identify fraud, abuse, and data quality issues in real-time with AI-powered pattern recognition.

Smart Alerting

Configure custom alerts that trigger instantly when anomalies are detected. Get notified via your preferred channels.

Custom Scripts

Write your own detection rules or let AI agents learn from your data and automatically deploy optimized scripts.

Real-Time Processing

Process data streams at scale with sub-millisecond latency. Built for high-throughput enterprise workloads.

Enterprise Reliability

99.99% uptime SLA. Bank-grade security with data encryption at rest and in transit. SOC 2 Type II compliant.

Full Observability

Complete visibility into your data pipeline. Track metrics, monitor agent performance, and debug issues.

How It Works

From Connection to Detection in Milliseconds

01

Connect Your Data Sources

Integrate with HTTP endpoints, Kafka, message queues, or any data connector. Set up your input stream in minutes.

02

Configure Detection Logic

Write custom detection scripts or enable AI learning mode. The agent learns your data patterns and builds optimized rules.

03

Millisecond Execution

Rules process in <1ms. Alerts and triggers fire instantly. Set up actions that execute at light speed.

04

Continuous Learning

AI improves performance over time. Gets faster and more accurate daily. Monitor in real-time with zero maintenance.

Detection Scripts

Write in CEL

Deploy custom detection logic using Google's Common Expression Language. Simple, powerful, and fast.

Advanced Fraud Detection 
// Flag suspicious patterns: high-value txn + new account + velocity spike + history check
ml.rcf_score("txn_features", "fraud_model") > 0.9
  && cel.("amount") > 5000
  && history.count("user_id", "1d") < 5
  && math.stats("hourly_txn_counts").mean > 3 * math.stats("hourly_txn_counts").stdev
PII Governance & Masking Pipeline 
// Detect PII, mask it, verify mask applied, hash for audit trail
let detected = governance.is_pii("payload")
let masked = mask("ssn", "ssn") != "ssn"
let hash = hash.sha256("user_id")
detected && masked && hash.size() == 64
Multi-Vector Abuse Detection 
// Combine RCF anomaly score with rate limiting + geographic anomaly
(ml.rcf_score("behavior_vector", "abuse_detector") > 0.85
  || cel.("requests_per_minute") > 100)
  && cel.("location_score") > 0.7
  && cache.get("user:block:" + cel.("user_id")) == null
Data Quality & Schema Validation 
// Validate schema, check required fields, sanitize, enrich with computed fields
let enriched = set("data", "processed_at", now())
let valid = cel.has("user_id") && cel.has("email")
let email_valid = cel.("email").matches(r"^[\w.-]+@[\w.-]+\.\w+$")
let stats = math.stats(enriched."latency_history")
valid && email_valid && stats.stdev < 200

Or let AI monitor execution and continuously improve scripts.

Infrastructure

Zero-Friction Integration

High-performance connectors and sinks. Wire-speed data ingestion and output.

Data Connectors

HTTP Kafka RabbitMQ AWS SQS Google Pub/Sub PostgreSQL CDC

Data Sinks

PostgreSQL MongoDB Elasticsearch Kafka AWS S3 Custom Webhooks

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