Semantic layer +

verified SQL trace

Ask in plain English and inspect the verified SQL trace. Every answer maps to your semantic layer and warehouse.

Three steps

no engineers required

Numerical — CeGJl89Y7cNTGiv2rSzc

01

Ask

Ask

Type a question in the chat interface. "What's our net dollar retention by cohort?" or "Which accounts churned last quarter that had declining usage?".

Type a question in the chat interface. "What's our net dollar retention by cohort?" or "Which accounts churned last quarter that had declining usage?".

Numerical — CeGJl89Y7cNTGiv2rSzc

02

Numerical — CeGJl89Y7cNTGiv2rSzc

02

Mora generates

Mora generates

Mora translates your question into SQL, runs it against your connected data sources, and returns the answer, with a chart, a summary, and the underlying query.

Mora translates your question into SQL, runs it against your connected data sources, and returns the answer, with a chart, a summary, and the underlying query.

Numerical — CeGJl89Y7cNTGiv2rSzc

03

Numerical — CeGJl89Y7cNTGiv2rSzc

03

Drill down

Drill down

Ask follow-up questions to go deeper. "Break that down by plan tier." "Exclude trial accounts." "Show me the trend over the last 6 months." Each follow-up refines the analysis in real time.

Ask follow-up questions to go deeper. "Break that down by plan tier." "Exclude trial accounts." "Show me the trend over the last 6 months." Each follow-up refines the analysis in real time.

Numerical — CeGJl89Y7cNTGiv2rSzc

03

Drill down

Ask follow-up questions to go deeper. "Break that down by plan tier." "Exclude trial accounts." "Show me the trend over the last 6 months." Each follow-up refines the analysis in real time.

Everything you need
in one single platform

Natural language to SQL

Mora translates plain English questions into optimized SQL — across Stripe, Salesforce, HubSpot, your warehouse, and every other connected source. You see the generated SQL and can edit it if you want.

Multi-source reasoning

Ask a question that spans billing and CRM data in a single query. "Which accounts in our enterprise segment have had 3+ support tickets and declining MRR?" Mora joins across sources automatically.

Context-aware follow-ups

Mora remembers the context of your conversation. "Now show me just Q4" or "Add product usage data" — each follow-up builds on the previous query without starting over.

Automated visualizations

Every answer comes with the right chart — Mora selects the visualization type based on the data shape. Time series get line charts. Comparisons get bar charts. Distributions get histograms. You can customize or override.

Answer explanations

Mora doesn't just return numbers. It explains what the data shows, highlights notable patterns, and flags anomalies — so you can share insights with your team without additional analysis.

Query history and saved questions

Every question you've asked is saved and searchable. Pin your most-used queries, share them with teammates, or schedule them to run on a recurring basis.

Built for the moments
that drive revenue

Revenue team standup

Start your morning by asking "what happened to our revenue yesterday?" and get a complete daily briefing — new MRR, churned accounts, expansion, contraction — in seconds.

Board prep

Ask the questions your board will ask before they ask them. "What's our burn multiple?" "How does NRR compare to last quarter?" "What's our pipeline coverage for Q3?" Prepare in minutes, not days.

Ad-hoc investigation

A metric looks off in your dashboard. Instead of filing a ticket, ask "why did churn spike in March?" and Mora breaks down the contributing factors — by segment, plan, cohort, or any other dimension.

Cross-functional alignment

Sales asks about pipeline. Finance asks about cash. Product asks about usage. Everyone asks Mora — and gets consistent, source-of-truth answers from the same data.

Here's what
you should know

Here's what
you should know

Supported models

GPT-4o and Claude for natural language understanding and SQL generation

Response time

Typical answers in 3–8 seconds depending on data volume and query complexity

Conversation memory

Full session context maintained in every conversation for follow-up questions

Query targets

Any connected data source: Stripe, Salesforce, HubSpot, Snowflake, BigQuery and more

SQL transparency

Every generated query is visible, editable, and exportable

Access controls

Role-based permissions determine which data sources and tables each user can query

Supported models

GPT-4o and Claude for natural language understanding and SQL generation

Response time

Typical answers in 3–8 seconds depending on data volume and query complexity

Conversation memory

Full session context maintained in every conversation for follow-up questions

Query targets

Any connected data source: Stripe, Salesforce, HubSpot, Snowflake, BigQuery and more

SQL transparency

Every generated query is visible, editable, and exportable

Access controls

Role-based permissions determine which data sources and tables each user can query

Answers in seconds
no SQL, no tickets

Connect your stack, ask questions, and get answers without waiting on an analyst.