Conversational Analytics
Fully Embedded. Fully Controlled.
Let users ask questions, generate KPI summaries, detect anomalies, and surface insights directly inside your product — powered by your AI endpoint and governed by your infrastructure.
- Built for SaaS teams shipping AI in production.
Built for SaaS teams shipping AI in production.
Trusted by engineering teams building analytics experiences in production.
What AI Analytics Looks Like Inside Products
Reveal delivers conversational intelligence that feels native to your product — not bolted on.
Actionable Intelligence, Not Just Answers
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Conversational Q&A
Translate natural language into optimized queries against your data.
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Explainable Results
Show how insights were derived — with query transparency and visual context.
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KPI Summaries
Instantly summarize performance across dashboards and datasets.
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Anomaly Detection
Identify unusual patterns before users know to ask.
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Recommended Actions
Surface next-best steps based on detected trends.
This isn’t generic LLM output.
It’s data-aware, application-embedded intelligence.
From Question to Insight — Inside Your App
1. Users Ask
User asks a question in plain language
2. Reveal Interprets
Reveal interprets and constructs optimized queries
3. Query Runs
The query runs securely against your data
4. Results Return
Results return with explanation and visualization
5. Saved
Insights can be saved directly into dashboards
Enterprise Ready
Enterprise-Grade Governance & Predictable Cost
AI analytics must be safe, auditable, and financially controllable. Reveal runs inside your infrastructure and respects your existing security model.
Role-Based Access
Pass user roles via JWT and enforce access automatically using your existing policies.
Full Auditability
Log every AI-generated query — including who asked what and which data was accessed.
Token Usage Limits
Set usage caps per tenant or user to prevent runaway AI costs.
Model Flexibility
Use OpenAI, Azure OpenAI, private LLMs, or enterprise-hosted models.
Flexible Deployment
Cloud-hosted, private cloud, or fully self-hosted — including air-gapped environments.
AI that operates within your governance framework — not outside it.
You Control the AI. Not Us.
Reveal does not host your AI. Reveal does not train your models. Reveal does not store your data.
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Customer-Controlled
You supply the AI endpoint and manage all models for Reveal AI interactions. -
No Reveal-Hosted AI
We never store data, train models, or use RAG or vector databases. -
Explicit Opt-In
AI is off by default. You enable it via configuration or code.
AI analytics — on your terms.
AI Enhances Your Dashboards. It Doesn’t Replace Them.
Dashboards remain essential for monitoring known KPIs.
AI accelerates exploration and contextual understanding.
Together, they create:
- Embedded dashboards + AI side-by-side
- Click-to-Ask-AI on any metric
- Inline anomaly surfacing
- Full drilldown continuity
Conversational insight built into visual workflows.
Under the Hood
Reveal AI operates as an extension of the Reveal SDK:
API-Driven
Architecture
Endpoint-Based AI
Execution
Tenant-Aware
Query Construction
Security-Layer
Integration
No External Data
Extraction
AI embedded at the architectural level — not wrapped around it.
What Reveal AI Is — And Isn’t
Reveal AI Is:
- Embedded in your application
- Governed by your access policies
- Powered by your AI endpoint
- Auditable and cost-controlled
Reveal AI Is Not:
- A hosted AI analytics platform
- A bolt-on chat interface
- A black-box LLM wrapper
- A vendor-controlled data pipeline
This is embedded AI infrastructure — not an AI experiment.
Frequently Asked Questions
AI analytics uses artificial intelligence to automatically analyze data, identify patterns, and generate insights that help users understand trends and make better decisions.
In the context of embedded analytics, AI capabilities allow users to ask questions about their data, explore insights using natural language, and uncover trends without needing advanced data analysis skills.
Reveal AI combines conversational analytics, automated insights, and embedded dashboards to help software products deliver more powerful data experiences directly inside their applications.
Conversational analytics allows users to interact with data using natural language instead of traditional queries or dashboards.
Users can ask questions such as:
“What caused the revenue drop last quarter?”
“Which customers had the highest growth this month?”
Reveal AI translates these questions into optimized queries against your data and returns clear, explainable results directly within your application.
This makes analytics accessible to a broader range of users without requiring technical expertise.
Reveal AI is designed specifically for embedded analytics environments.
Instead of operating as a separate analytics tool, Reveal AI works alongside embedded dashboards and reporting within your application.
Users can:
- Ask questions about their data
- Explore AI-generated insights
- Drill into dashboards for deeper analysis
This combination of AI exploration and structured dashboards allows users to move seamlessly between discovering insights and monitoring key metrics.
Yes. Reveal AI is built to be fully embedded into software applications.
Using Reveal’s SDKs and APIs, developers can integrate AI-powered analytics directly into their product interfaces, allowing users to explore insights without leaving the application.
This ensures that AI capabilities feel like a native feature of your software rather than an external tool.
Reveal AI is designed to operate within secure enterprise environments.
Organizations maintain full control over data access and governance through existing authentication systems, role-based permissions, and security policies.
Key security capabilities include:
- Row-level data access control
- Authentication integration
- Tenant isolation for SaaS platforms
- Full query auditing for AI-generated insights
This ensures that AI-powered analytics respects the same security and governance rules applied across your application.
Reveal AI is designed to provide transparent and explainable insights rather than opaque “black box” responses.
Every AI-generated result is derived from queries executed against your underlying data sources. Users can review the context of each insight, explore supporting dashboards, and drill deeper into the underlying data.
This approach ensures analytics remains trustworthy while still benefiting from AI-powered discovery.
AI-powered embedded analytics helps software companies deliver more valuable data experiences to their users.
Key benefits include:
- Faster insight discovery through natural language questions
- Reduced manual reporting and analysis
- Improved product engagement through interactive analytics
- More accessible insights for non-technical users
By combining AI with embedded dashboards, organizations can transform raw data into actionable intelligence directly within their applications.
AI-powered embedded analytics is most valuable for software companies that want to provide data insights directly inside their products.
Common use cases include:
- SaaS platforms providing analytics to customers
- Fintech applications analyzing financial activity
- Supply chain software tracking operational performance
- Customer success platforms monitoring product usage
By embedding AI analytics into their applications, these companies enable users to explore data and make decisions without leaving the product environment.
Ready to Embed AI with Enterprise-Grade Control?
Ship conversational analytics safely. Without surrendering governance. Without surrendering cost visibility.
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