Why Most AI Data Initiatives Fail to Deliver
Connecting a generic AI directly to your database often leads to a dangerous combination of plausible-sounding but fundamentally incorrect answers. This erodes trust across your organization and stalls progress. Here’s why:
They Don't Know Your Business
Competitive advantage comes from the ability to act on unique institutional knowledge. But this knowledge—the specific metrics, data, and terminology a business runs on—is the exact context generic AI tools lack. Without knowing your definition of an "active user," for example, they deliver plausible but fundamentally incorrect answers.
Their Logic is Hard to Verify
AI can generate complex queries quickly, but without a clear semantic foundation, that logic is difficult to inspect or explain. When teams can’t verify how an answer was produced, trust erodes — and people stop asking meaningful questions.
High Cost & Complexity to Maintain
Building AI features from scratch is a major engineering effort that doesn’t end at launch. Without a durable context engine, teams are stuck in a cycle of prompt tuning, patching broken logic, and rebuilding trust — pulling focus away from core product development.
The Foundation for Trustworthy AI
Our platform is built on a simple premise: trustworthy AI isn’t about better prompts — it’s about better context. Credible gives teams the tools to build, maintain, and deliver trusted context — grounded in shared meaning and served wherever analysis happens. It’s designed around four key pillars:
Context That Reflects Analytical Intent
Credible delivers context where analysis happens — in dashboards, applications, APIs, and AI agents. At delivery time, context reflects the analytical intent of the question being asked, so answers align with how teams actually analyze data. This makes analysis flexible without becoming inconsistent, and allows different tools and agents to work from the same underlying understanding.
Shared Meaning, Made Explicit
That context is grounded in shared meaning. Credible gives teams the tools to aggregate definitions, metrics, and institutional knowledge from across the data ecosystem and encode them into semantic models. By making meaning explicit — rather than buried in queries or tribal knowledge — teams can collaborate with confidence and reuse logic across people, tools, and workflows.
Built to Evolve With Your Business
Shared meaning isn’t static. Credible surfaces ambiguity and edge cases as real questions are asked, providing clear signals and workflows that help teams refine and evolve their models over time. Teams stay in control, improving shared understanding through a governed, human-in-the-loop process as the business changes.
A Purpose-Built, Open Foundation
Credible is built on Malloy, a powerful, open-source language designed to encode meaning clearly and compactly. With Malloy, humans and AI work from the same readable, auditable logic, while the compiler handles the complexity of generating correct SQL. This keeps context explainable, testable, and trustworthy at scale.
This foundation is what empowers you to unlock deeper, novel, and truly Credible insights—cutting across data silos to uncover the trends, anomalies, and correlations that drive real business value.
Your Data Insights, Available Everywhere
Credible’s context engine is available wherever analysis and decisions happen — from deep exploration to intelligent, product-embedded AI.
Explore in Shared Workspaces
Credible provides analysis workspaces where you can explore data on your own or share work with your team. Ask questions, build artifacts, and extend existing analysis with shared context powered by governed semantic models. As teams work, their interactions help refine and evolve the underlying models.
Connect Your Own Agents via MCP
Give your AI agents access to the same context your teams trust. Using the open Model Context Protocol (MCP), you can connect custom LLM agents and chatbots to Credible’s APIs, enabling data-aware features inside your products and internal workflows.
An Extensible, Open-Source Foundation
Built on a mature open-source ecosystem, Credible gives you flexibility without lock-in. Extend the platform, build new integrations, or contribute back — on your own terms.
