Sifflet Tech Stack
AI-powered data observability platform connecting data quality to business impact
Sifflet operates a data observability platform built on an AI agent architecture (Sentinel, Sage, Forge) that detects anomalies, diagnoses root causes, and suggests fixes. The stack reveals a modern, multi-cloud data infra: Snowflake, BigQuery, Redshift, dbt, Airflow, Databricks — standard for observability. The project list signals two growth vectors: expanding North American sales (sales enablement, building NA business, new customer implementations) and scaling the core product (lineage model merging, ingestion optimization, database performance monitoring). Hiring is accelerating across engineering and go-to-market, with cost and scalability challenges indicating they're hitting volume limits on the ingestion engine.
Tech Stack 32 technologies
What Sifflet Is Building
◆Challenges
- Expanding presence in north america
- Scalability challenges
- Infrastructure costs
- Monitoring database performance
- Scaling ingestion engine for large instances
- Reducing ingestion engine cost
▲Active Projects
- Ai agents positioning
- Sales enablement materials
- Building north american business
- Implementations for new customers
- Extend the agent that runs in customer networks with support for new sources to be monitored
- Implement tooling to monitor database performance
- Ingest infrastructure, product and sales data into a single data warehouse
- Build lineage model merging data from multiple sources
- Optimize ingestion engine queries to reduce cost
- Fetch query history for root cause analysis
