I built an open-source AI data layer that connects any LLM to any data
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
In plain words
This open-source AI data layer connects any large language model to any data source, enabling teams to build conversational data interfaces. It centralizes context management through instructions, dbt models, Tableau, and code, then lets users query data to generate charts, dashboards, and reports through an agentic interface. The product includes agent tracing, quality scoring, and Slack integration for observability and governance. It's designed for teams that want structured, controlled AI-powered data chat without the limitations of earlier text-to-SQL approaches.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context (instructions, dbt, code, AGENTS.md, Tableau) and governance. Users can chat with their data to build charts, dashboards, and scheduled reports — all via an agentic, observable loop. With slack integration as well! * Centralize context management: instructions + external sources (dbt, Tableau, code, AGENTS.md), and self-learning * Agentic workflows (ReAct loops): reasoning, tool use, reflection * Generate visuals, dashboards, scheduled reports via chat/commands * Quality, accuracy, and performance scoring (llm judges) to ensure reliability * Advanced access & governance: RBAC, SSO/OIDC, audit logs, rule enforcement * Deploy in your environment (Docker, Kubernetes, VPC) — full control over infrastructure GitHub: github.com/bagofwords1/bagofwords Docs / architecture / quickstart: docs.bagofwords.com
Pricing, as stated on its site
Free — Open-source project hosted on GitHub. No pricing information found for the product itself; it appears to be freely available as open-source software.
checked September 2026 · prices change
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