Structured data grounding
Connect AI to structured data so answers are grounded in verifiable records rather than unverified text.
Baselight
RivendicaBaselight is a unified data layer that connects humans and AI to structured, verifiable data. It helps users analyze public and private datasets with natural language, SQL, visualizations, and auditable outputs.
What Baselight is
Baselight is a unified data layer for humans and AI. It connects language models and people to structured, verifiable data so analysis can stay grounded in source material instead of relying on guesses.
The product combines a public data catalog, an AI assistant, and a studio for SQL, AI, and visualization work. Its stated goal is to make insights explainable and auditable for individuals, teams, journalists, consultants, and developers who need data they can trace back to its origin.
Core capabilities
Verifiable, auditable analysis
Support explainable results and auditability by keeping the reasoning tied to source data and traceable outputs.
Unified analysis workspace
Combine SQL, AI, and visualizations in one workspace for analysis and reporting workflows.
Public and private data together
Browse a catalog of public data alongside private data that you upload, then work across both in the same environment.
AI-assisted querying
Use natural language to analyze data without needing SQL for every question, while still producing structured results.
MCP access for models and agents
Expose the catalog to external models and tools through MCP connections for agentic workflows.
Where Baselight fits
Internal copilots and team search
Use Baselight to let internal users ask questions in natural language while keeping answers tied to structured, traceable data.
Journalism and fact-checking
Use the catalog and AI assistant to investigate public datasets, verify claims, and build data-backed stories with traceable figures.
Consulting and reporting
Upload client or company data, combine it with public datasets, and use SQL or AI to produce analysis and dashboards.
Developer and agent workflows
Use MCP connections and the structured catalog to ground autonomous agents in verifiable context instead of static text.
Pros and Cons
Pros
- Connects AI to structured, verifiable data instead of leaving models to guess from text alone.
- Supports explainable and auditable outputs, which matters for fact-checking and review workflows.
- Combines public datasets, private uploads, querying, and visualization in one workspace.
- Offers plan options for individuals, teams, and enterprise buyers, including a free tier.
- Supports MCP access, which can fit agent and developer workflows.
Cons
- The public pages do not provide detailed documentation for all integrations, workflows, or supported data sources.
- Some usage details are still presented at a marketing level, so readers may need to evaluate the product directly to understand fit for their stack and data volume.
FAQ
What is Baselight used for?
Baselight positions itself as a unified data layer that connects AI and humans to structured, verifiable data. The homepage and pricing page suggest it is useful for grounded analysis, natural-language querying, and shared data work, but the source does not describe a separate setup flow in detail.
Does Baselight support MCP connections?
The pricing page states that Baselight includes access to the catalog from an LLM via MCP, and the homepage says developers can query structured data through MCP connections and integrate verified data into autonomous agents.
What pricing options are available?
The pricing page describes a free Starter plan, a Builder plan, a Teams plan with a minimum of 5 seats, and an Enterprise plan with custom pricing. It also notes that limits can be topped up or adjusted depending on the plan.
How do team limits work?
The pricing page says teams and Enterprise users get individual limits per user for storage, processing, and AI assistant usage rather than a shared pool.
What can Baselight AI do?
Baselight AI preview is described in a product post as an AI Chat experience that can analyze examples such as AI-related stocks and NBA games, while also showing reasoning that users can audit. The source does not document every available dataset or workflow.
Quick Facts
- Category
- Data platform
- Primary users
- Individuals, teams, journalists, consultants, analysts, agents, and developers
- Core workflow
- Query structured data with natural language, SQL, and visualizations
- Pricing
- Free Starter plan; paid Builder, Teams, and Enterprise options
- Access method
- Web app with MCP support
- Source domain
- baselight.ai
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