Agentic analytics workspace
Ask a hard question. Get an answer you can audit.
Bridgr reads your files and picks the right analysis for each question. It builds the graph it needs on the fly, then shows you exactly how it got there. No migration. No standing graph database.
What makes it different
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Route, do not funnel
The agent decides whether each question is graph shaped or table shaped. You never pick a tool before you know the answer.
Route and rationale appear in the receipt on every run.
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One approval, then it runs
You confirm the data mapping once. After that the analysis runs start to finish with no mid run checkpoints.
Mapping approval is the only human gate.
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Your data lake stays where it is
Each analysis builds a small, bounded graph from just the slice it needs, then discards it. Nothing is bulk loaded and nothing is migrated.
Ephemeral per analysis graph, scoped and disposable.
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Every number traces to a cell
Answers are synthesized from executed notebook output, not from a model summarizing your files. Open the cell that produced any figure.
Question battery graded 6 of 6 on grounded in cells.
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Documents are evidence, not a silo
PDFs and text are extracted into typed records and graph entities with exact character offsets. Click a claim, land on the source span.
Citations resolve against the exact source span.
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Inference is labeled, never disguised
What the documents actually say is drawn solid and cited. What the system infers beyond the text is drawn dashed and badged. The two never merge.
Extracted equals cited. Projected equals labeled inference.
Every analysis leaves a receipt
Sources read, quality flags, the route the agent chose and why, the scope it worked on, the model revision, and the running cost.
If a graph probe blew its budget and fell back to a table, the receipt says so.
Read 4 files · 10,500 work orders · claim rate 6.1% This question is graph shaped · built a graph · 65 nodes Model revision 3 · showing 65 of 2,140 Estimated cost $0.14
Five surfaces
- AskPut the question in plain language.
- Link AnalysisExplore entities and relationships on the canvas.
- AnalyzeWatch the notebook build and execute.
- AnswerRead the finding with its receipt and citations.
- AutomatePromote a run to a repeatable job. The newest surface.
How it works
From a folder of files to an answer you can open up and check.
- 1
Add your sources
Spreadsheets, Parquet, JSON, databases, PDFs, and text all come in the same door. Extraction and profiling start immediately and visibly. Anything unreadable is recorded as a limitation, never as fake success.
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Confirm the mapping
The agent proposes how your fields map to entities and relationships. You confirm once, or edit it first in the Ontology Studio. This is the only place the product asks for your approval.
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Ask in plain language
No query language, no route picker, no assumption sign off. The agent profiles the evidence and proceeds.
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The agent picks the shape
Traversal, communities, paths, and lineage questions get a graph. Aggregation, trends, and segmentation stay tabular. Documents get extracted first, then routed on the result. The safe default is tabular.
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Read the answer and the receipt
The answer is synthesized from the notebook cell that produced it. Every document claim resolves to an exact source span. The receipt shows the route, the scope, the model revision, and the cost.
The canvas is ephemeral on purpose
Every analysis builds a small bounded graph from the slice it needs. It runs Cypher against that graph, renders it, then discards it. Heavy algorithms and persistence are policy gated tiers.
FAQs
Do I have to migrate my data?
No. Nothing is bulk loaded and nothing is copied into a standing database. Each analysis builds a small graph from the slice it needs, then discards it.
What file types can I load?
CSV, Excel, Parquet, JSON, PDF, plain text, and SQLite databases. They all come in the same door. Extraction and profiling start as soon as a file lands.
How much do I have to configure before asking a question?
One mapping confirmation. The agent proposes how your fields map to entities and relationships, and you confirm it. That is the only checkpoint.
Do I need to know Cypher or SQL?
No. Plain language only. The agent writes and runs the query itself, and the cell it executed stays open for inspection.
Can I force a question down the graph route?
No, and that is deliberate. Routing is agent owned and always visible in the receipt. You steer by asking differently or by editing the model.
How do I know the answer is not invented?
Answers come from executed notebook cells, not from a model summarizing your files. Document claims carry exact character offsets. Open any figure and read the cell that produced it.
What happens when the data cannot answer the question?
You get an Inconclusive result, split between what was concluded and what is still a gap. A question outside the data gets an explicit refusal.
Do I need an API key?
Subscription first. Bridgr uses your Claude Code subscription when it is present. An API key with metered credits is the fallback. Cost stays visible in both modes.
Is my data sent anywhere?
No. Bridgr deploys on your infrastructure, in your own Docker environment. There is no Bridgr cloud and nothing is uploaded to us. Your files, your graphs, and every result stay on machines you control.
One exception, stated plainly: when the AI agent reasons over a question, it calls Claude under your subscription or API key. That call carries only the excerpts the agent is working on. Run with the agent off and nothing leaves the box.
What is not built yet?
We publish this list on purpose. Three things are honestly not done:
- The Delta Lake connector is deferred. The SQLite database connector proves the seam.
- Graph persistence beyond an analysis is policy gated and off by default. That is a design decision, not a missing feature.
- Scheduled automation runs on promote, run, and history. Cron triggers are next.
No questions match. Try a different word.