Upcoming demo days on
“How SaaS Companies Build & Scale Their Data Stack”
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7th August
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Register Here
Hevo’s fully managed ELT platform moves data from your diverse development, product, and GTM systems to your data warehouse, driving innovation and operational excellence.
Unify product telemetry, user logs, and subscription data from 150+ sources at scale for feature adoption, churn prediction, and A/B test evaluations.
Consolidate data from CI/CD, code repositories, APM, and infrastructure logs to build dashboards for monitoring and analysis.
Sync marketing, sales & billing data to map complete customer journeys, optimize sales strategies, & identify up-sell or cross-sell opportunities.
Combine ticketing, in-app feedback, customer success, and product usage data to identify at-risk accounts and refine support strategies proactively.
Utilize pre-built connectors to synchronize data from databases, third-party APIs, & SaaS applications, without writing code. Automatic schema mapping simplifies complex data structures, delivering accurate data at scale.
Protect sensitive user data, intellectual property, and operational metrics with end-to-end encryption, field-level masking, and comprehensive audit logs. Engineered to support SOC2 Type II, GDPR, & CCPA/CPRA compliance.
Process application log, user event, and API call data without performance degradation. Deliver clean, consistent data with a zero-maintenance, auto-scaling architecture that adapts to fluctuating data volumes.
reduction in platform costs
Accuracy Ensured through Hevo’s fault-tolerant architecture
“Developing an in-house solution comparable to Hevo would’ve definitely required significant expenditure both in terms of time & money. Hence we’re extremely happy to have Hevo on our side.”
Principal Engineer
"The Hevo support is pretty incredible. They help a lot with all kinds of problems and questions, and they seem to have huge value for my time. Dealing with questions or issues in Fivetran was very frustrating. In Hevo, the responses are lightning fast and very supportive."
Data Engineer
Cost saved for 2X data volume
