Any MCP client
Fluree publishes an MCP endpoint any compatible client can consume — Claude, ChatGPT, Bedrock, LangChain, CrewAI, or a custom agent. No vendor lock-in on the LLM side.
Conversational Analytics
Conversational analytics that doesn’t hallucinate.
Ask any question across every data source in your organization. Get verified, source-cited answers in seconds. Build live dashboards on the fly. Automate work with AI agents grounded in governed, provable data — not statistical guesses.
Trusted by
Before
T + 3–5 days- 01File a ticket with the BI team.
- 02Analyst stitches CRM + billing + support.
- 03Receive a static deck. It’s already stale.
- 04Ask a follow-up. Start over.
60–80% of dashboards built this way go unused.
Fluree
After
T + 3 seconds↓ asked
“Which customers are about to churn?”
- Live dashboard across 4 systems.
- Verified SPARQL under every metric.
- Every number traces to a row.
Delivered via MCP. Works with Claude, ChatGPT, Bedrock, and any compatible client.
Definition
What is conversational analytics software?
Conversational analytics software lets anyone ask questions of enterprise data in plain English and get verified, source-cited answers — with dashboards generated on demand instead of built in advance.
Traditional BI can only answer the dashboards someone thought to build. Forrester finds analysts lose 12 hours a week searching siloed data; 60–80% of dashboards go unused. Plugging an LLM directly into databases produces confident answers that are frequently wrong — the model doesn’t understand how your data relates.
Fluree takes a different path. An agent retrieves the semantic model, learns the classes and relationships, translates the question into verified SPARQL, and executes against governed data. Every answer comes back with the query logic and citations attached.
In Fluree’s April 2024 study, GraphRAG for GenAI Accuracy, graph-native retrieval reached 95%+ accuracy on enterprise questions — where “chat with your data” tools plateau near 80%.
What Makes Fluree Different
Three things “chat with your data” wrappers can’t do.
Retrieves by relationships — not by fragments.
Most conversational analytics tools chunk documents and retrieve by statistical similarity. Fluree traverses your knowledge graph with structured context, source lineage, and relationship-aware evidence.
Why it matters
Because “statistical similarity” isn’t the same as truth.
Vector RAG
Top-k fragments with conflicting context and no relationship path.
GraphRAG
Customer → Contract → Amendment → Policy
with cited lineage.
Three steps.
One platform.
From a raw source to a governed knowledge graph — with answers that trace back to the row they came from.
Connect any source.CSV, API, Postgres, Snowflake, Salesforce — Fluree ingests it as-is. No schema migration. No pipelines to maintain.
The graph builds itself.Entities resolve, duplicates merge, and relationships infer in place — no modeling marathon, no manual ontology.
Answers, with receipts.Ask in plain language. Every answer traces back to the exact row it came from — for humans, agents, and apps alike.
How do conversational answers become production BI?
Every answer ships with the SPARQL that produced it. Data teams inspect the query, promote it to BigQuery, Databricks, or any BI stack, and schedule it as a standing report — no rebuild required.
Dashboards, auto-generated
For complex prompts, Fluree generates React-based dashboards, charts, and narrative summaries tuned to the question — turning weeks of dashboard work into hours.
Promote verified SPARQL
Verified queries can be promoted to BigQuery, Databricks, or any BI stack — and scheduled as machine-to-machine reports and alerts.
See where Fluree stands.
Every answer traced. Every source cited. Compare the platforms enterprises shortlist for conversational analytics.
Questions Your Data Team Gets Asked Every Week
They used to disappear into a backlog. Now they get answered — with the SPARQL attached.
ask ›
“Which of our top 20 customers are at risk of churning next quarter?”
ask ›
“What are the five worst-performing products, and why?”
ask ›
“Produce an executive dashboard showing ROI growth and current risks.”
ask ›
“I’m new to the organization — help me understand our data.”
ask ›
“What camera-trap evidence do we have for nocturnal species, 2018–2022?”
ask ›
“Total CRE exposure over $500K in downtown markets with LTV above 75%.”
ask ›
“Which of our top 20 customers are at risk of churning next quarter?”
ask ›
“What are the five worst-performing products, and why?”
ask ›
“Produce an executive dashboard showing ROI growth and current risks.”
ask ›
“I’m new to the organization — help me understand our data.”
ask ›
“What camera-trap evidence do we have for nocturnal species, 2018–2022?”
ask ›
“Total CRE exposure over $500K in downtown markets with LTV above 75%.”
In Production
Global financial services leader
“Semantic tagging went from error-prone and manual to quality-controlled and AI-driven. User trust in the data portal came back.”
~500K
documents
100%
automated tagging
Hundreds
analysts served daily
10×
knowledge base growth
“In the age of AI and agents, everybody deserves AI that works. Let’s make sure we get it done.”
Read the full case studyThe conversational analytics playbook.
Webinars, whitepapers, and articles that walk through the architecture, the evidence, and the production path.
Webinar replay
Live demo
Unified Intelligence — Ask the Questions That Matter, Across Every System That Matters
A live MCP agent conversation spanning Salesforce, SAP, spreadsheets, and SQL — at 90% less cost than traditional integration.
Watch replay
Thesis
Executive downloadIntroducing Business Intelligence Without the BI Software
The shift from pre-built dashboards to conversational, governed answers — and what it means for BI teams.
Read the articleThe complete guide to retrieval, knowledge graphs & LLMs.
Download whitepaper
Architecture
The Power Trio Reshaping BI: GraphRAG, MCP & LLMs
Why these three together produce agents that actually work in production — end-to-end architecture.
Read the articleFAQ
GenBI is the AI-native BI stack that replaces manual dashboard creation with proactive, conversational, on-demand intelligence. It combines a conversational interface, a semantic layer, a knowledge graph, and data-centric security.
No. Conversational analytics software lets people query governed business data in natural language and get cited answers and dashboards. Conversation intelligence tools analyze recorded customer conversations — calls, chats, support tickets — for sentiment and agent performance. Fluree is the former: analytics over your enterprise data, not analysis of conversations.
Traditional BI requires pre-built dashboards and analyst time for every new question. Fluree generates dashboards on demand from natural-language prompts spanning multiple systems — in one governed experience.
ThoughtSpot works primarily on warehouse schemas. Fluree queries a knowledge graph with explicit semantic relationships, handles unstructured data, and embeds security at the data layer.
Fluree queries governed data first using verified SPARQL against the knowledge graph, then applies generative AI on the results. Every answer can be traced to the underlying query and source records.
No. Business users can query in plain English. Data teams can optionally review and promote the resulting SPARQL into production workflows.
Any MCP-compatible client — Claude, ChatGPT, Amazon Bedrock, LangChain, CrewAI, or your own custom agents. Fluree publishes a standard MCP endpoint, so there’s no lock-in on the LLM side.
Yes. Conversational analytics accelerates dashboard creation by producing verified query logic that your team can deploy into BigQuery, Databricks, or any BI tooling.
Recognized by Gartner
Stop building dashboards. Start getting answers.
60–80% of dashboards go unused. Fluree gives every person in your organization the answers they need — instantly, verifiably, from actual data.