Sift Hub provides a cloud‑native data integration platform that unifies SaaS APIs, on‑premise databases, and event streams into a single analytics layer. It offers a low‑code pipeline builder, pre‑built connectors, and a real‑time streaming engine that normalizes and enriches data into a scalable columnar lake, accessible via dashboards, ad‑hoc queries, and APIs with built‑in governance. The solution targets data‑centric enterprises seeking consolidated, near‑real‑time business metrics.
Funding
$5.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises often rely on multiple, siloed data sources—such as SaaS APIs, on‑premise databases, and event streams—making it difficult to achieve a single source of truth. Disparate formats and manual ETL processes increase latency, introduce errors, and hinder timely operational reporting. Consequently, decision makers lack real‑time visibility into key performance indicators across the organization.
Solution
Sift Hub delivers a cloud‑native data integration platform that consolidates heterogeneous data streams into a unified analytics layer. The service provides pre‑built connectors and a low‑code pipeline builder to ingest, normalize, and enrich data in near real‑time. Processed data is stored in a scalable columnar lake and exposed through configurable dashboards, ad‑hoc query interfaces, and API endpoints. Built‑in governance features enforce schema consistency, data lineage, and role‑based access controls, ensuring compliance with security standards. By centralizing data processing and visualization, Sift Hub enables operational teams to generate actionable insights without maintaining separate ETL stacks or custom reporting tools.
Target Audience
Primary customers are data‑centric enterprises—such as finance, retail, and manufacturing firms—and their data engineering, analytics, and operations teams that require a consolidated, real‑time view of business metrics.
Features
- Over 150 native connectors for SaaS applications, relational databases, message queues, and IoT streams, with support for custom API integration via SDK
- Visual ETL designer that supports drag‑and‑drop transformations, schema mapping, and data enrichment using Python or SQL scripts
- Real‑time streaming engine built on Apache Flink/Kafka that processes events with sub‑second latency and automatic fault tolerance
- Columnar data lake storage optimized for analytical queries, with automatic partitioning and tiered cold‑storage options
- Interactive dashboard builder with drill‑down charts, KPI widgets, and alerting rules configurable via a web UI
- RESTful and GraphQL APIs for programmatic data access, enabling downstream applications to consume curated datasets
- Enterprise‑grade security: end‑to‑end encryption, SSO/SAML integration, audit logging, and fine‑grained RBAC
- Auto‑scaling compute resources managed by Kubernetes, ensuring performance under variable workloads