Your team built the Modern Data Stack. But you're still the 'human API', answering the same questions, writing the same queries, cleaning up AI hallucinations. Cartographer automates the know-how of your data warehouse, so you can finally do what you were hired to do: drive strategic impact.
THE BOTTLENECK PROBLEM
In most organizations, the data team spends 80% of their time acting as 'human APIs', answering repetitive questions about where data lives and what it means.
80% of your team's time goes to answering 'Where do I find X?' and 'How do I join X to Y?' You're not building value, you're directing traffic.
You spent months documenting the warehouse. It was outdated before you finished. Now nobody trusts it, and they just Slack you instead.
You gave them Looker/Tableau. Now you have 47 definitions of 'Revenue' and more tickets asking 'which number is right?' Self-service without governance is chaos.
You tried the new AI/BI tools. They make things up, wrong columns, impossible joins, inflated numbers. Without semantic grounding, AI is confidently wrong.
THE CARTOGRAPHER ENGINE
Cartographer goes beyond semantic layers, it discovers entities, relationships, and causality by analyzing how your data is actually used. The foundation for AI that doesn't hallucinate.
Cartographer Engine
Ready to scan
6 AI agents • 4 hours vs 4 months • Automatic semantic discovery
Beyond semantic layers
Cartographer reads how your data is actually used and produces a context graph: entities, measures, relationships, time patterns, causal hints. No interviews, no LookML drafts.
Stop writing the same query
Because Cartographer maps relationships and cardinality automatically, the platform handles joins itself. Your team stops being the destination for 'Total Sales by Region' for the hundredth time.
No more hallucinations
Every column the system writes exists. Every join is one the data actually supports. Every aggregation follows your business rules. Validated, not invented.
Find the hidden definitions
The system surfaces de-facto metrics calculated in siloed spreadsheets across departments. Spot when Marketing and Finance are computing 'Churn' differently, then standardize.
WHAT THE GRAPH CONTAINS
A grounded foundation everything else queries. Built from how your warehouse is actually used, not from interviews.
Tables classified by their role: objects, events, mappings.
KPIs inferred from how aggregations actually appear in real queries.
JOIN paths mapped from usage, with cardinality, so fan-out errors don't happen.
The right timestamp columns and granularities detected automatically.
Dimensions surfaced from how teams already slice the data in practice.
Drill paths and significance signals synthesized across the graph.
GOVERNANCE & OWNERSHIP
Stop managing metric definitions across spreadsheets, Jira tickets, and SQL comments. Manage the Business Logic Layer in one place.
Certify discovered measures. A 'Certified' badge surfaces on the Living Map so the org knows the data team has verified the underlying SQL.
Data team owns quality and availability. Business owns performance. Clear accountability, fewer blame games when a number moves.
Grant access to a strategy layer without exposing the raw tables underneath. Node-level and branch-level visibility controls.
Aggregation happens inside the statistical engine. Users see insights without ever touching sensitive row-level data.
HOW THE WORK CHANGES
Your Cartographer-powered context graph feeds directly into the Living Map. Business leaders can explore, drill down, and analyze, without asking you for help. That's the 80% reduction in ad-hoc requests.
Business users navigate the Living Map without SQL knowledge
KPI Drilldown generates insights using your blessed definitions
Deep Analysis runs statistical tests on your validated schema
Schema changes auto-update the Living Map, no manual sync
YOUR WORK → THEIR SELF-SERVICE
You build the context graph
Business explores without you
Drilldown
Analysis
Co-Pilot
80% fewer ad-hoc requests to your team
THE PLATFORM
Your context graph powers every intelligence capability. See how each part of the platform uses your work.
Your context graph, visualized for business self-service
Business users explore without asking you
Statistical rigor without manual SQL
Auto-discover flows, find leaks, compare cohort retention
AI grounded in YOUR context graph
THE ROI
4 hrs
Versus four months of manual modeling, interviews, and LookML drafts.
80%
The questions the data team used to answer by hand now route through the graph.
Auto
The Living Map stays current as the warehouse evolves. No manual sync step.
TECHNICAL DETAILS
MindPalace integrates with your existing stack, not against it.
Connects to Snowflake, BigQuery, Redshift, Azure SQL, PostgreSQL
Works alongside dbt, Looker, enhances your existing stack
Builds the context graph from real query history, not just schema
Statistical analysis powered by scipy, statsmodels, pandas
Role-based access control with audit logging
Your data never leaves your warehouse
INTEGRATES WITH YOUR DATA STACK
What OpenAI's internal data agent teaches about AI-native BI, why LLMs should never calculate your metrics, and what the underlying context graph layer looks like.
OpenAI's internal data agent looks like a chatbot. Inside, it is a context graph. Here is what AI-native BI actually requires, and what most teams will miss.
Most AI-native BI tools let a language model calculate your business metrics. That is a category error. Here is the architecture we built instead, and why.
A Decision Context Graph is the missing layer between your warehouse and your decisions. Here is what it is, how we build one in four hours, and why it matters now.
See how Cartographer can transform your data team from a service desk to the intelligence architects they were meant to be.