Scriptly Helps Pharmacies Identify Trends in Real Time with Reveal
Embedded Analytics Security
Enterprise-grade security for embedded analytics and AI-powered insights
Reveal delivers embedded analytics designed for security-first SaaS and regulated environments without exposing data to third-party SaaS platforms, fragile iFrame architectures, or uncontrolled AI models.
Why Embedded Analytics Security Matters
Embedding analytics is not just a UI decision. It is a security and architectural one.
When analytics become customer-facing, it expands your application’s attack surface. Data access, identity propagation, tenant isolation, and AI governance all become critical design considerations.
Data Sovereignty
Reveal enforces tenant isolation at query execution, preventing cross-tenant data access in shared environments.
AI Context Control
Reveal restricts AI access to governed data only, reducing the risk of prompt injection and unauthorized data exposure.
Compliance Ready
Reveal supports GDPR, HIPAA, and SOC 2 requirements through controlled data access, auditing, and flexible deployment models.
For B2B SaaS and regulated industries, security failures do not just impact compliance; they erode customer trust, increase churn risk, and slow enterprise adoption.
Common Security Risks in Embedded Analytics and How Reveal Mitigates Them
Risk
Impact
Reveal Mitigation
Cross-tenant data access due to weak isolation
TENANT ISOLATION
Tenant context enforced at query execution for every request
Inconsistent authentication across analytics and application
AUTHENTICATION MODEL
Inherits your existing auth model with no parallel user systems
Analytics running outside your security perimeter via iFrames
EMBEDDING ARCHITECTURE
Runs inside your application via SDK, not external containers
AI accessing unrestricted or sensitive data
AI ACCESS CONTROL
AI operates within your permission model and access controls
Analytics tools that fail compliance requirements
COMPLIANCE ALIGNMENT
Supports GDPR, HIPAA, and SOC 2 through architecture
CORE ARCHITECTURE
Reveal’s Embedded Analytics Security Architecture
Reveal embeds directly into your application using SDKs, not external SaaS containers or iFrames, giving security teams full operational visibility.
SDK-First Integration
Built to operate within your application’s security model and infrastructure.
- Operates within your application’s security and deployment model
- Does not own or monetize customer data
- Authentication, authorization, and data access remain under your control
- Deployment flexibility without sacrificing security
Operational Security & Infrastructure Safety
Reveal is designed to operate cleanly within enterprise environments:
- Compatible with existing proxies, load balancers, and gateways
- Explicit, configurable dependencies with no undisclosed data transmission
- Designed to run behind reverse proxies and enterprise firewalls
Authentication, Authorization & Data Access Control
Reveal enforces your existing security model; it does not replace it.
- SSO, OAuth, and SAML integration
- Role-based and row-level security are inherited from the host application
- Secure user context propagation across analytics interactions
- No shadow user or permission systems
No Shadow User or Permission Systems
Reveal doesn’t introduce a separate authentication or authorization layer. Your existing identity system remains the source of truth, preventing permission drift and keeping access control consistent across your application and analytics.
Single Source of Truth
No Permission Drift
Reduced System Complexity
Auditability, Monitoring & Operational Visibility
Security teams do not lose insight when analytics are embedded.
- Visibility into analytics query execution
- Deterministic behavior under load
- Compatibility with existing logging and monitoring tools
- Troubleshooting without exposing sensitive customer data
CORE ARCHITECTURE
Secure AI Analytics Customer Controlled by Design
AI in analytics must be governed, not experimental.
Fully Opt-In
AI features are disabled by default and must be explicitly enabled. You control scope, permissions, and usage at every level.
Configurable Per Tenant
Configure AI per tenant using your own LLM endpoints, including private or on-prem models, aligned with your security requirements.
Controlled Data Access
AI operates within your permission model and governed data access using metadata, aggregated results, or scoped datasets without bypassing controls.
No Third-Party Exposure
No customer data is sent to third-party AI services unless explicitly configured. No raw customer data is sent by default.
No raw customer data is sent to third-party AI services by default.
Deployment Models That Reduce Security Risk
- Cloud deployments
- Hybrid architectures
- Fully on-prem environments
Security-sensitive teams do not need to compromise modern analytics experiences to maintain control.
Compliance & Governance Readiness
Reveal supports compliance by architecture:
- Data residency and minimization controls
- Clear separation of analytics tooling and data ownership
- Auditing and monitoring support
- Deterministic exports with controlled execution contexts
Analytics remains secure from dashboard to export.
Embedded Analytics Security Use Cases
Learn why intuitive, self-service, embedded analytics matter
View All Blogs
Ensuring Security with Embedding AI-Powered Analytics
Martin Atanasov
Security with embedded analytics gets more complex when AI enters the picture. This article breaks…
Scalable Analytics: How to Build for Growth Without Breaking BI
Martin Atanasov
Traditional BI tools often fail to handle increasing user counts and expanding data volumes, resulting…
Embedded Analytics for SaaS Companies
Martin Atanasov
The best way to deliver insights in your SaaS product is to embed them directly…
Frequently Asked Questions
Reveal embeds analytics via SDKs inside your application architecture, not through external SaaS containers or iFrames. Analytics executes within your security perimeter, inheriting your authentication, authorization, and tenant isolation model.
By contrast, many SaaS-based embedded analytics tools operate outside the host application, introducing third-party data exposure, opaque execution paths, and limited auditability. Reveal avoids that model entirely, making secure embedded analytics a foundational design choice rather than an afterthought.
Reveal runs inside your infrastructure, cloud, hybrid, or fully self-hosted, without taking ownership of customer data. All queries execute against your existing data sources, using the same security context enforced by your application.
Reveal does not replicate, monetize, or retain customer data outside your environment. This architecture ensures embedded analytics security without expanding your data exposure surface.
No.
Reveal does not persist customer data in external systems or route analytics through third-party services. Execution, caching, and exports occur within controlled environments defined by your deployment model.
This approach eliminates the common risks associated with SaaS analytics platforms and aligns with embedded analytics security best practices for regulated and enterprise environments.
Yes.
AI capabilities can be enabled or disabled at the tenant, environment, or deployment stage level. This allows organizations to adopt AI analytics selectively while maintaining governance, compliance, and risk control.
Yes.
Reveal supports fully self-hosted deployments, allowing organizations to run analytics entirely within their security perimeter. This includes environments with strict regulatory or sovereignty requirements and aligns with on-prem analytics security expectations.
Reveal enforces tenant isolation at runtime for every analytics request. Tenant context is explicitly propagated and validated before query execution, preventing cross-tenant data access by design.
There is no shared execution layer or global query context. This makes Reveal suitable for customer-facing, multi-tenant embedded analytics in B2B SaaS applications with strict security requirements.
Reveal inherits your application’s authentication model and does not introduce a parallel identity system. Users access analytics through the same identity, roles, and permissions already defined in your product.
SSO, OAuth, and SAML integrations are supported, with secure user context propagation across dashboards and interactions. This eliminates policy drift and reduces the attack surface.
AI features in Reveal are opt-in and governed by the same permission model as analytics data. AI-powered analytics operates within defined access controls and never bypasses your security rules.
Reveal supports customer-controlled AI models, including private and on-prem deployments. By default, no raw customer data is sent to third-party AI services, directly addressing embedded analytics AI security concerns.
Reveal supports compliance through architecture rather than bolt-on controls. Data access, residency, and minimization are enforced within your environment, with a clear separation between analytics tooling and data ownership.
Auditing, monitoring, and deterministic exports are designed to support regulatory reviews and enterprise procurement processes.
No.
Security enforcement is part of Reveal’s execution model, not layered on top of it. Authentication, authorization, and tenant isolation are handled deterministically, allowing analytics to remain responsive and predictable under load.
Reveal integrates with existing logging and monitoring tools, allowing security teams to observe analytics execution without exposing sensitive customer data.
This enables troubleshooting, audit readiness, and operational visibility without introducing blind spots or unmanaged systems.
