ETL-C as a Service
Managed platform for context-first data processing. Contextual joins, adaptive pipelines, and semantic understanding - without building infrastructure from scratch.
Based on our proprietary ETL-C Framework
Your data is missing context
Traditional ETL strips the business context from your data. Records lose their meaning, relationships disappear, and AI systems hallucinate to fill the gaps. Building context infrastructure from scratch takes months.
Data without meaning
"Transaction: $500" tells you what. "Customer's first purchase after 3 weeks of browsing, during a promotion, from mobile" tells you why.
Integration pain
"Jane Smith" in CRM, "J. Smith" in transactions. Traditional joins fail. Manual matching takes forever.
AI hallucination
Without context, AI models fill gaps with assumptions. Your RAG applications return confident but wrong answers.
Infrastructure burden
Building context infrastructure means vector databases, graph stores, embedding pipelines. Months of work before value.
"Context Engine: 40% faster integration, 3x improvement in AI accuracy."
See contextual joins in action
Traditional joins match on exact keys. Context Engine matches on meaning. Click records to see how semantic matching works.
Click any record to see how Context Engine matches it
Building connected context
Context Engine automatically discovers and maps relationships across your data. Hover over nodes to explore connections.
Context as a managed service
Context Engine delivers the ETL-C Framework as a managed platform. Focus on your data, not infrastructure.
Contextual Join Engine
Semantic matching across datasets using embeddings + metadata. "J. Smith" matches "Jane Smith" with 95% confidence. Audit trail for every match. No more manual record linking.
Adaptive Pipeline Orchestration
Pipelines that dynamically adjust based on context signals. Financial data processes differently during market volatility. Customer segments get different enrichment. Business events drive behavior.
Managed Context Store
Unified storage for semantic context. Vector database for embeddings, graph database for relationships, time-series for temporal patterns. One API to query it all.
AI-Ready Data APIs
Semantic query interface optimized for RAG applications. Natural language queries return contextual results. Streaming updates for real-time context.
From data to intelligence
Context Engine integrates with your existing data infrastructure and progressively adds semantic understanding.
Connect
Connect your data sources - warehouses, lakes, APIs. Context Engine ingests and begins context extraction.
Contextualize
Automatic embedding generation, relationship detection, and semantic annotation. Manual enrichment where needed.
Join
Run contextual joins across your datasets. Match records by meaning, not just keys. Review and approve matches.
Serve
Query contextual data through APIs. Feed your AI applications with semantically-rich data. Monitor and refine.
Plans for every scale
Starter
$2,000/month
Up to 1M records contextualized. 100K contextual joins. Basic Context Store. API access.
Pro
$8,000/month
Up to 10M records. 1M contextual joins. Full Context Store. Streaming APIs. Priority support.
Enterprise
Custom
Unlimited records. On-premise deployment. Custom integrations. Dedicated support. SLA.