Stop Building a BI Tool.
Start Shipping World-Class
Analytics Features

Your customers are demanding more than just data exports. They want actionable, embedded insights inside your application. But what starts as "adding a few charts" quickly spirals into a full-blown, resource-draining engineering project.

We partner with SaaS companies to build secure, scalable, and high-impact customer-facing analytics. We provide the architecture, pre-built models, and implementation expertise to help you deliver a market-leading analytics experience, faster.

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Building In-App Analytics is Harder Than It Looks.

SaaS teams often underestimate the complexity of delivering embedded analytics. Whether you're building a specific feature or implementing a framework, you face a common set of pitfalls that waste time, burn budget and damage customer trust.

Challenge 1: Adding a Complex Analytical Feature (Marketing Attribution):

You think you're just adding a dashboard, but you're actually building a complex data modeling engine from scratch. Without deep expertise, this often leads to:

  • Brittle, oversimplified models that fail to meet customer expectations.

  • Noisy, untrustworthy results due to a poor data foundation.

  • Months of engineering "plumbing" instead of delivering value.

  • Features that don't scale and instead break under increased data volume.

Challenge 2: Implementing a Framework (Cube, Embeddable, Looker Embedded)

You've chosen a powerful framework like Cube.js, but you're discovering that implementation is fraught with risk. DIY attempts frequently result in:

  • Catastrophic security holes from poorly handled multi-tenancy.

  • Slow, unreliable dashboards that frustrate customers due to a lack of performance tuning.

  • Unnecessary reinvention of caching, access control, and BI layers.

  • A fragile, misaligned architecture that creates a disconnect between your data and product teams.

In both scenarios, the outcome is the same: a high-cost project that fails to deliver strategic value and erodes customer trust.

Deliver High-Impact Analytics,
Without the Headaches.

We bring both the strategic product thinking and the deep technical expertise to turn embedded analytics into a scalable, secure and valuable feature - not a liability.

  • Pre-Built, Modular Models

    We leverage our library of proven, pre-built models (multi-touch marketing attribution, Cube automation and others) to dramatically accelerate your time-to-market.

  • Expert Framework Implementation

    As experts in Cube.js, dbt, and Looker, we ensure your embedded analytics framework is perfectly aligned with your warehouse, orchestration, and CI/CD strategy.

  • Proven Architectural Patterns

    We design secure, scalable architectures with robust tenant isolation, performance tuning, and pre-aggregation strategies from day one.

Go from Roadmap to Revenue Fast with Pre-Built Analytics

  • Implement Sophisticated Marketing Attribution Out-of-the-Box : Our multi-touch marketing attribution package includes multiple industry-standard models (first-touch, last-touch, time-decay), pre-built connectors for Google Ads, Meta Ads and other ad networks and logic to handle complex conversion cycles, LTV and multi-currency reporting.

  • Deploy a Governed Semantic Layer Instantly : Provide your customers with a world-class, self-service analytics experience without reinventing the wheel. Our frameworks include fully defined metrics layers and LookML models ensuring consistent, reliable, and easily explorable data from go live.

  • Integrate Conversational AI on Day One : Our open-source LangChain SQL Agent allows you to connect a conversational AI chatbot directly to your governed Looker semantic layer, enabling your customers to ask natural language questions and transforming a static dashboard into an interactive assistant.

Embedded Analytics is Only as Good as its Implementation

  • Architect a Secure, Multi-Tenant Data Model from Day One. The biggest risk in embedded analytics is data leakage. We design and implement a robust, production-grade security model using best practices for authentication and row-level security, ensuring one customer's data is never exposed to another.

  • Design for Performance and Scale : Don't let slow dashboards frustrate your customers. We design and tune high-performance caching and pre-aggregation within Cube, Embeddable and your framework that delivers insights in seconds, not minutes. By optimizing how the framework queries your data warehouse, we prevent bottlenecks and ensure a fast, reliable user experience.

  • Integrate Seamlessly with Your Existing development Workflows. Your analytics feature shouldn't be another data silo. We ensure your embedded analytics framework integrates directly with your existing dbt models and CI/CD pipelines, creating a unified development workflow with automated testing and validation and preventing fragile deployments.

Secure, Scalable and Seamlessly Integrated By Design

  • Architect a Secure, Multi-Tenant Data Model from Day One. The biggest risk in embedded analytics is data leakage. We design and implement a robust, production-grade security model using best practices for authentication and row-level security, ensuring one customer's data is never exposed to another.

  • Design for Performance and Scale : Don't let slow dashboards frustrate your customers. We design and tune high-performance caching and pre-aggregation within Cube, Embeddable and your framework that delivers insights in seconds, not minutes. By optimizing how the framework queries your data warehouse, we prevent bottlenecks and ensure a fast, reliable user experience.

  • Integrate Seamlessly with Your Existing development Workflows. Your analytics feature shouldn't be another data silo. We ensure your embedded analytics framework integrates directly with your existing dbt models and CI/CD pipelines, creating a unified development workflow with automated testing and validation and preventing fragile deployments.

From Vision to Reality:
How We Helped Insighta Build a Multi-Tenant Analytics Platform

  • Insighta needed to build a scalable, multi-tenant marketing attribution application for their diverse client base.

  • They knew that achieving their ambitious goals required external expertise in data engineering and analytics enablement

  • Our Partnership delivered:

    • A Scalable Multi-Tenancy Architecture using dbt and Dagster.

    • Customized Conforming Data Layers to integrate disparate data sources like Shopify and NetSuite.

    • Predictive Analytics & ML Workflows to deliver actionable insights.

    • Rapid Deployment and Automation to accelerate the onboarding of new clients.

With a background in building multi-tenant solutions for clients in the marketing technology industry, Rittman Analytics were the ideal partner to help Insighta make our product vision a reality.
— Matthiew Liu, Co-Founder, Insighta

Ready to Build a Data Function That Drives Growth?

Let's discuss how our strategic partnership can help you achieve your specific goals. A discovery call is the first step to understanding if we're the right fit to move your data capabilities forward