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Why Fig Is Different

Cortex and Genie translate your questions into database queries. Analytics tools build dashboards for analysts. Fig is different: it governs how decisions get made across every person and every AI agent in your company — grounded in your own data, enforced by your own rules, and calibrated by what actually happened in your business.

Stop Paying the Wrong Tool to Do the Right Job.

Traditional platforms bolt AI onto reporting. Fig was built from the ground up as the decision layer — using your own data, your own rules, and a causal model that actually learns.

Traditional Semantic Layer

dbt, Looker, AtScale

The Semantic Layer Describes Data. It Doesn't Make Decisions.

Semantic layers define what your metrics mean. They standardize definitions and expose them to BI tools. That's useful — but it's half the job. The other half is knowing what to do when a metric moves, which accounts are responsible, and what to act on. A semantic layer has no concept of decision, action, or outcome. It's a dictionary, not an operator.

AI Bots on Traditional BI

Tableau Pulse, Power BI Copilot, Snowflake Cortex, Databricks Genie

Don't Overpay Your BI Platform for an AI Add-On.

Tableau Pulse, Power BI Copilot, Snowflake Cortex — these are AI features bolted onto platforms you're already paying for. They translate questions to SQL. They don't know your business rules, your causal model, or your approved metric definitions. You're paying a premium for a natural language interface on top of dashboards. That's not a decision layer. It's a chatbot on a chart.

The Modern Stack

Purpose-built for decisions

The Right Tool for Each Job. Not One Platform for All of Them.

Your warehouse is for storing and aggregating data — Snowflake and BigQuery are excellent at this. Your BI tool is for visual reporting. Fig is for the layer those tools were never designed to handle: learning what causes what in your business, governing which definitions are approved, and making consistent decisions across every person and every AI agent. Build your stack with purpose-built tools. Stop paying premium prices for AI add-ons that weren't designed to think about your business.

Fig vs. Snowflake Cortex

Cortex is a Snowflake-native AI layer. Fig is warehouse-agnostic, governed, and an installable skill for any agent.

Capability	Snowflake Cortex	Fig
Warehouse support	Snowflake only	BigQuery, Snowflake, Databricks, Redshift, Postgres, and more
Metric governance	No versioning or approval chains	Versioned, approved metric definitions with conflict detection
Business entity graph	No entity model	Accounts, customers, and products modeled as first-class graph nodes
Flow automation	No workflow automation	Signal → Decide → Act flows — scheduled or trigger-based
Outcome calibration	No feedback loop	Decisions measured against outcomes — model updates with what actually happened
AI agent skill (MCP)	Not an installable skill	Fig's MCP skill works with Claude, GPT, LangChain, CrewAI, or any agent
Business policies & rules	No policy layer	Business context stored and enforced on every query

Warehouse support

Snowflake Cortex

Snowflake only

Fig

BigQuery, Snowflake, Databricks, Redshift, Postgres, and more

Metric governance

Snowflake Cortex

No versioning or approval chains

Fig

Versioned, approved metric definitions with conflict detection

Business entity graph

Snowflake Cortex

No entity model

Fig

Accounts, customers, and products modeled as first-class graph nodes

Flow automation

Snowflake Cortex

No workflow automation

Fig

Signal → Decide → Act flows — scheduled or trigger-based

Outcome calibration

Snowflake Cortex

No feedback loop

Fig

Decisions measured against outcomes — model updates with what actually happened

AI agent skill (MCP)

Snowflake Cortex

Not an installable skill

Fig

Fig's MCP skill works with Claude, GPT, LangChain, CrewAI, or any agent

Business policies & rules

Snowflake Cortex

No policy layer

Fig

Business context stored and enforced on every query

Fig vs. Databricks Genie

Genie translates natural language to SQL inside Databricks. Fig has a causal graph, metric governance, and works with any warehouse.

Capability	Databricks Genie	Fig
Warehouse support	Databricks only	Any warehouse — BigQuery, Snowflake, Databricks, Redshift, Postgres
Decision model	Natural language → SQL	Causal relationship tree — knows what causes what, with measured coefficients
Metric versioning	No governance or approval chains	Approved metric definitions, version history, conflict detection
Flow automation	No workflow automation	Signal → Decide → Act — automated end-to-end on schedule or trigger
Business entity model	No entity resolution	Accounts and customers resolved across Salesforce, Stripe, Shopify, and more
Outcome feedback	No feedback loop	Measures whether decisions worked — model calibrates from real outcomes
AI agent skill (MCP)	Not an installable skill	Installable in any AI agent via MCP — one skill, every agent in your org

Warehouse support

Databricks Genie

Databricks only

Fig

Any warehouse — BigQuery, Snowflake, Databricks, Redshift, Postgres

Decision model

Databricks Genie

Natural language → SQL

Fig

Causal relationship tree — knows what causes what, with measured coefficients

Metric versioning

Databricks Genie

No governance or approval chains

Fig

Approved metric definitions, version history, conflict detection

Flow automation

Databricks Genie

No workflow automation

Fig

Signal → Decide → Act — automated end-to-end on schedule or trigger

Business entity model

Databricks Genie

No entity resolution

Fig

Accounts and customers resolved across Salesforce, Stripe, Shopify, and more

Outcome feedback

Databricks Genie

No feedback loop

Fig

Measures whether decisions worked — model calibrates from real outcomes

AI agent skill (MCP)

Databricks Genie

Not an installable skill

Fig

Installable in any AI agent via MCP — one skill, every agent in your org

Fig vs. Analytics Agents (Hex, Tableau Pulse, ThoughtSpot)

Analytics tools answer questions for analysts. Fig governs decisions for every person and every AI agent in the company.

Capability	Analytics Agents	Fig
Decision model	NL-to-SQL on top of dashboards	Governed causal knowledge graph — knows causes, not just correlations
Metric governance	No approval chains or versioning	Blessed definitions, approval chains, and conflict detection
Who it works for	Analysts and BI consumers	Every person AND every AI agent in the company via MCP
Flow automation	No workflow automation	Recurring decisions automated Signal → Decide → Act
Outcome learning	No feedback loop	Calibrates from observed outcomes — every decision informs the next
Business entity graph	No entity model	Customers, accounts, and products as graph nodes — resolved across sources
Business policies	No policy enforcement	Your business rules enforced on every query — no analysis contradicts your logic

Decision model

Analytics Agents

NL-to-SQL on top of dashboards

Fig

Governed causal knowledge graph — knows causes, not just correlations

Metric governance

Analytics Agents

No approval chains or versioning

Fig

Blessed definitions, approval chains, and conflict detection

Who it works for

Analytics Agents

Analysts and BI consumers

Fig

Every person AND every AI agent in the company via MCP

Flow automation

Analytics Agents

No workflow automation

Fig

Recurring decisions automated Signal → Decide → Act

Outcome learning

Analytics Agents

No feedback loop

Fig

Calibrates from observed outcomes — every decision informs the next

Business entity graph

Analytics Agents

No entity model

Fig

Customers, accounts, and products as graph nodes — resolved across sources

Business policies

Analytics Agents

No policy enforcement

Fig

Your business rules enforced on every query — no analysis contradicts your logic

Fig Works with Your AI Agents

Install Fig's decision-making skill in any AI agent via MCP. One skill — your metric definitions, business policies, entity graph, and causal relationships — available in every agent your team runs.

Claude

GPT

LangChain

CrewAI

And any agent that supports the Model Context Protocol (MCP)

The Fig Difference

Fig is not an analytics tool. It is the decision-making skill layer — built from your data, governed by your rules, calibrated from your outcomes.

Built from Your Data, Not Generic Knowledge

Fig's causal graph is learned from your specific business — your metrics, your historical outcomes, your entity relationships. Not pretrained on public data. Not hallucinated. Your business, modeled precisely.

Governed, Not Just Answered

Every metric definition goes through an approval chain. Every business policy is versioned. Every query is checked against your rules. Fig doesn't just answer questions — it enforces how your organization has decided to answer them.

One Skill for Every Agent

Fig's MCP skill installs into Claude, GPT, LangChain, CrewAI, or any agent your team runs. One install. Your full business context — metric definitions, entity graph, policies, causal history — available everywhere.

Decisions That Learn from Outcomes

Most tools stop at the answer. Fig measures whether the decision worked and updates its model from what actually happened. Every closed loop makes the next decision better than the last.

Flows That Run Without You

Define a signal, wire in a decision rule, attach an action. Fig runs the full Signal → Decide → Act sequence on a schedule or when a trigger fires — so recurring decisions don't require a human in the loop every time.