Everything you need to add context to your OT data, query across sources, and build a semantic layer that reflects your operations.
Ask questions in plain English. Our AI interprets your intent and generates a structured query that you can review and adjust before execution. Full transparency, full control.
Live tag values delivered in under 2 milliseconds. NATS pub/sub replaces polling — your dashboards update the instant a value changes. Subscribe to any tag, any plant, with wildcard patterns.
Query data at the source without moving it. Conduit dispatches queries to Splunk, MQTT, and OPC-UA in parallel, merging results without data replication.
Join events and metrics across different systems in a single query. Correlate alarms from Splunk with process data from MQTT and OPC-UA to find root causes.
DuckDB-Powered Time-Aligned Joins
Correlation detected: 94% match | Join key: equipment | Engine: DuckDB
Build your UNS from actual usage patterns, not theoretical models. Source bindings, tag proposals, and formula definitions grow the namespace organically as your team queries data.
Built from actual usage, not theoretical models
Routing Intelligence, Collaboration & Context
Beyond data querying, the platform learns your organization's decision trees, routes questions to the right experts, and builds persistent context from every interaction.
AI that learns your organization's decision trees. It watches how questions flow, discovers who actually resolves them, and progressively takes over routing — from pure observation to fully autonomous.
Questions reach the right expert in seconds, not days. The AI acts as a smart chief of staff — clarifying intent, routing with confidence scores, and synthesizing answers from multiple experts when needed.
Your expertise, proven through actual work. Build a context profile that captures what you know, what you contribute, and how you solve problems. It moves with you.
Senior OT Engineer
Built on a 3-database architecture with Neo4j for graph relationships, PostgreSQL for relational data, and pgvector for semantic search. 18 backend services, 72,000+ lines of production code, and 5,500+ tests across two interconnected platforms.
Additional capabilities that make Conduit enterprise-ready.
Multi-tenant RBAC, JWT authentication, mTLS and NATS TLS for mesh communication, and certificate rotation without restarts.
Learn from user corrections with confidence scoring. Auto-promotion pipeline promotes patterns to golden templates when thresholds are met.
Pluggable AI backend supporting Claude, OpenAI, Azure OpenAI, Ollama, and Mock providers.
Redis-backed DAG caching with SHA-256 topology hashing. Identical query structures resolve instantly on repeat execution.
Dispatch known fields immediately, return partial results, and update when remaining sources respond. Progress over perfection.
Correction pattern analysis with confidence scoring. Tracks query corrections and promotes successful patterns to golden templates.
Security isn't an afterthought. It's the foundation of how Conduit works. Your data stays in your network, every query is audited, and access is controlled at every layer.
Conduit queries data in place — no data replication, no centralized data lake, no data movement across network boundaries.
Every query is authenticated and authorized. No implicit trust based on network location. Mutual TLS between all components with certificate-based identity.
Complete query logging with user attribution, timestamp, data sources accessed, and results. Full audit trail for compliance and forensic analysis.
Multiple overlapping security layers: network segmentation, application-level access control, mutual TLS between services, and complete query audit trails.
All data in transit encrypted with TLS 1.3. Support for mutual TLS authentication.
Scoped API keys for translators with automatic rotation and revocation.
See how Conduit can transform your industrial data operations. Get a personalized demo from our team.