Query
Which customers are likely to churn, and what evidence should the team trust?
AI-driven analytics and data intelligence for enterprises
Turn raw data into
trusted business insight.
Datapane.ai combines GenAI ETL pipeline building, an ontology layer, and data lineage mapping to help enterprises create a modern analytics foundation that is scalable, governable, and ready for AI.
Question
How much premium freight have we spent because of third party vendor’s quality holds during the crisis window?
01Autopilot
Ask with context.
Get the path, proof, and solution.
Autopilot plans the work, gathers the right context, reasons across structured and unstructured data, then produces an answer your team can inspect and operationalize.
Enterprise promptWhich customers are most likely to churn next quarter?
Catalog
Storage
Documentation
Application data
Plan
Find the useful context across CRM, support, contracts, catalog metadata, and meeting notes.
Reason
Connect account health, product incidents, renewal timing, usage, spend, and policy constraints.
Solve
Return the ranked list, explain the evidence, and deploy the dashboard or workflow for follow-through.
02Positioning
Questions become products.
Answers become operations.
DatapaneAI is built for teams that do not want another search box. They need a system that understands business context, explains the evidence, and turns repeated decisions into working assets.
DatastoresRedshift Snowflake Databricks AWS Glue BigQuery Azure Synapse Salesforce Data 360 SAP Datasphere BI DashboardsPower BIDashboard and BI context TableauDashboard and BI context Business ContextDocuments Confluence Meetings
Data warehouse
Polaris Catalog
Unity Catalog
Glue Data Catalog
Coming soon
Coming soon
Coming soon
Coming soon
Policies and files
Team knowledge
Audio and transcript
Business teams wait too long
Answers stay trapped behind ticket queues, SQL backlogs, and disconnected tools instead of reaching decision-makers in time.
Engineers spend time on plumbing
ETL, joins, schema drift, and handoffs keep data teams buried in repetitive integration work instead of higher-value delivery.
Governance is hard to prove
Compliance, lineage, approvals, and policy enforcement stay fragmented across systems, making enterprise trust fragile.
Cloud cost shows up too late
Finance sees spend after the fact, without enough visibility into query behavior, team ownership, or operational waste.
03Six Platform Cards
Catalog, storage, docs,
and application data as context.
The platform connects every major enterprise surface into a living context layer. Agents use that context to answer questions, generate assets, and keep operations aligned with the source truth.
Platform & Ops 01Catalog Federation
Unify Glue, Snowflake, Databricks, and Redshift into one normalized catalog with resilient access.
Platform & Ops 02FinOps & Cost Explorer
Attribute cost to query behavior and give teams clearer operational visibility into usage.
Platform & Ops 03LLM Registry
Centralize model configuration so teams can swap runtime models without rewiring product logic.
Platform & Ops 04QuickSight & SageMaker
Bridge embedded BI and ML operations with smoother handoff into enterprise AWS workflows.
Platform & Ops 05Smart Integration Hub
Route requests to the right graph, lineage, quality, cost, or ontology surface from one integration layer.
Platform & Ops 06Notifications & Digests
Generate AI-assisted summaries, trend signals, and operational alerts for teams that need regular visibility.
04Six Pillars
Six pillars.
One context engine.
DatapaneAI brings catalog, ontology, intelligence, autopilot, pipelines, and operations into one loop: ask, understand, solve, deploy, monitor, and improve.
Super Catalog
Find trusted data across every catalog, see where it came from, and understand who can use it.
Structured + Unstructured Ontology
Understand how tables, documents, meetings, files, and operational records relate before a human has to map them.
Super Intelligence
Break a business question into agent steps, connect the evidence, and return a sourced answer you can trust.
Research Agent
Ask a multi-document question, let the agent search evidence, and get a cited answer with gaps clearly called out.
Intelligent Pipeline
Describe the data product you need, review the proposed steps, and approve a governed pipeline as it is built.
Intelligent Ops
Track cloud, data platform, and AI spend with live alerts, anomaly context, and guided savings actions.
05Capabilities
DatapaneAI
answers in action
Watch a question move from natural language into discovery, planning, sampling, charting, dashboard design, validation, and deployment inside the same governed workspace.
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06Capability Surface
Every capability
starts with context.
Analytics, governance, knowledge, ML, platform operations, and collaboration all share the same understanding of what your enterprise means.
Analytics & Exploration4 capabilities
Ask questions in plain English, get charts, SQL, and an assistant that can keep drilling into the result.
Conversational ETL that discovers schema, previews steps, and turns intent into executable preparation flows.
Compose pipelines from modular blocks while natural-language decomposition helps shape the underlying workflow.
Explore dimensions, pivots, and patterns across multiple engines through a guided interactive surface.
07Unprecedented Speed
From question
to governed solution.
Start with the data estate you already have. DatapaneAI builds the context, exposes the evidence, and helps teams ship usable dashboards, workflows, and decisions quickly.
Elastic by the second
Burst from a single analyst to thousands of concurrent agents, then scale right back down. You pay only for the questions you ask.
In place
Petabyte-ready, in place
Reason over lakehouse-scale data where it lives - no extracts, no sampling, no waiting on a nightly copy.
Enterprise-secure by default
Encryption, fine-grained access and immutable audit applied everywhere - security that scales with your data, not against it.
08Trusted Companies
Companies that trust
DatapaneAI
Teams use DatapaneAI to bring governed context, lineage, and automation into the analytics workflows they already rely on.
09Customer Stories
Teams adopting governed
workflow automation
Enterprise teams use DatapaneAI when AI needs to move beyond isolated retrieval and into repeatable, governed reasoning across the full data lifecycle.
★★★★★
Featured
datapane.ai gave our teams one shared layer across warehouses, documents, and operational systems instead of disconnected silos.
Director of Data EngineeringFortune 100 Retail Enterprise
★★★★★
This is the first experience where our governance team can actually trust AI because the context, lineage, and policy path are visible.
VP, Data PlatformsGlobal Automotive Manufacturer
★★★★★
We finally have a platform that explains what the agent saw, what it believed, and why it acted. That changed adoption speed completely.
Chief Data & Analytics OfficerLeading Financial Services Company
Initialize datapane.ai
Automate your
Workflow Ecosystem
Bring your data topology, governance requirements, and fragmented enterprise context. We’ll show how datapane.ai builds one shared ontology and knowledge graph around it.