Slow time-to-market
A simple analytics feature expands into months of backend work on performance, security, and flexibility instead of core product.
Embedded analytics
Data features your customers trust—without rebuilding the stack
Credible removes the data bottleneck with a governed model, built-in access controls, and a context engine delivered through APIs, SDK, and MCP.
Your team focuses on the experience. Credible handles definitions, governance, multi-tenancy, and scale.
The bottleneck
Modern product velocity meets fragile data infrastructure
Internal metric drift is damaging enough. Export it into your product and it erodes your customers' trust in you.
Inflexible experiences
Static charts give customers little room to explore. AI Q&A bolted on later lacks the context required for reliable answers.
Failure to scale
The solution that works for ten customers breaks at a thousand. Dashboards time out and queries fail under real usage.
Skyrocketing cost
Production-ready, multi-tenant data products require much more than a proof-of-concept chatbot. Brittle queries and prompt tuning become permanent overhead.
Capture, enrich, deliver
A governed foundation delivered into your product
Credible applies the same shared framework to product analytics, with capabilities designed for secure multi-tenant use cases.
Capture: one model for product data
Define metrics, dimensions, and relationships once. Dashboards, AI chat, and API responses all draw from the same source of truth.
Enrich: tenant controls built in
Declare tenant isolation at the model layer, version it with the model, and enforce it at query time instead of scattering security logic across application code.
#(secure)
given:
ALLOWED_TENANTS :: string[]
source: tenant_analytics is app_data extend {
where: tenant_id in $ALLOWED_TENANTS
measure:
#(doc) Active accounts for this tenant, shown on the Usage dashboard.
active_accounts is count(distinct account_id)
}Add #(doc) context so product AI uses the exact definitions shown in customer-facing experiences.
Deliver: context engine in your product
Serve governed meaning through APIs, SDK, and MCP. Embed dashboards, charts, AI chat, and data features with tenant isolation and access controls handled automatically.
Built for production
A foundation for better products
Give customers fast, trustworthy analytics while retaining governance and visibility across every user and query.
Built on open-source Malloy
Compose and reuse analytical patterns with clear logic. Models are portable, with no proprietary query language or lock-in.
Enterprise-ready by design
Multi-tenant isolation, fine-grained controls, and full audit logging are built in. Every query routes through versioned models you control.
Optimized for scale
Query optimization and caching control warehouse cost. Usage analytics reveal what customers actually value.
Developer-first workflow
Work with AI coding tools such as Cursor while Credible supplies governed context through MCP for Malloy queries and embedded code.
Ready when you are
From proof-of-concept to production without the rewrites.
See how Credible's context engine helps you ship analytics experiences your customers can trust.