Know your customer. Act on it faster.
Bring product, revenue, and support data into one foundation, so every team works from the same customer reality, without waiting on engineering.
to a working customer data foundation
faster from raw data to usable product and revenue insights
less data engineering effort on pipelines and transformations
to answer product and revenue questions across systems
Everything your software data foundation needs, built in
Bring product, revenue, and customer data into one system your teams can use immediately, without building and maintaining pipelines across tools.
Bring all systems that define your customer into one foundation, without building custom connectors.
- product databases and event streams
- CRM systems like Salesforce and HubSpot
- billing platforms like Stripe and Chargebee
- support tools like Zendesk and Intercom
- marketing and attribution data
Every system reflects the same customer, without manual reconciliation.
- unified identifiers across product, revenue, and support
- no duplication or conflicting records
- consistent definitions across every team
Trust is built into the foundation from the start.
- full lineage behind every metric
- access controls across datasets and teams
- consistent data policies across all use cases
Your teams work with usable data, not raw tables.
- customer 360 views
- usage and engagement datasets
- churn and retention models
- revenue and cohort analytics
The same foundation powers every tool, team, and workflow.
- product analytics tools
- finance and reporting systems
- support and success workflows
- internal APIs and applications
- AI and automation use cases
Built as a system, not stitched as a stack
Most teams assemble tools for ingestion, storage, transformation, and activation. It works until pipelines break, costs grow, and complexity slows everything down. LakeStack replaces that with one system where everything already works together.
Ingestion, transformation, and activation are already connected. Schema changes do not break downstream systems, and your team is not maintaining custom pipelines across tools.
One system replaces multiple tools across ingestion, warehouse, transformation, and activation. You are not managing vendors, integrations, or fragmented workflows.
Everything runs inside your cloud account. Your data does not move through external systems, and your security and compliance posture stays intact.
New sources and new use cases do not require rebuilding your foundation. The system adapts as your data grows, without adding complexity.
Product, finance, and support work from the same data. Metrics stay consistent, and decisions happen without reconciliation.
Choose how your data foundation works, before it slows you down
Every software company ends up building a data foundation. The real decision is how it gets built, how long it takes, and what it costs you over time.
What you’ll achieve once your data works
When your data foundation is already in place, new initiatives stop being data projects. They become product features, analytics, and decisions your teams can move on immediately.
See what is actually driving growth across your business.
- unified view of product, revenue, and customer health
- clear visibility into retention, expansion, and churn
- faster, more confident strategic decisions
Stop building data infrastructure. Start shipping product.
Understand how usage connects to revenue and retention.
Align revenue metrics with product reality.
Act on customer signals before issues escalate.
Focus on insights, not pipelines.
CRM, DMS & service ops data unified across 200+ dealerships for AI-ready reporting
LakeStack, built by Applify, runs entirely inside your cloud environment, so your data, infrastructure, and policies stay under your control as you scale analytics and AI across your product.
- No external SaaS layer, data stays within your environment
- No data routing outside your network or VPC
- No proprietary storage formats or vendor lock-in
- No custom pipeline engineering required to scale
- Unified control across ingestion, transformation, and access
- Real-time visibility into data movement and lineage
- Operates on your infrastructure, under your policies
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Experience how LakeStack works for software companies
In a short working session, we map your current systems, your key use cases, and show you exactly how a unified data foundation would look in your environment.
Frequently asked questions
LakeStack provides governed data spaces and role-based access controls, so data can be segmented and accessed at the appropriate level. This enables teams to serve analytics across different users or groups while maintaining controlled access to data.
LakeStack includes standardized transformation patterns and supports extensions for custom logic. Product-specific models, metrics, and transformations can be implemented on top of the foundation while maintaining lineage and governance.
Schema changes are handled automatically within the foundation. New fields or changes in structure do not break downstream datasets, so your analytics, reports, and features continue to work without constant rework.
Yes. LakeStack enforces role-based access control with support for column-level and row-level policies. Data access is governed across ingestion, transformation, and activation, ensuring consistent control across all use cases.
LakeStack serves governed datasets to BI tools, applications, APIs, and workflows from a single foundation. The same data layer supports internal reporting, operational use cases, and product-driven data access without requiring separate systems.
