Your AI Product Analyst
Connect PostgreSQL, MongoDB, BigQuery, Snowflake, Mixpanel, Amplitude, Stripe, and files. Ask product questions in plain English, save adoption dashboards, set watches on KPI shifts, and share stable views across product, growth, and leadership.
12.4K
+9.6%
68%
+4.2pp
82%
+1.8pp
Retention by Cohort
Top Sources
0x
fewer handoffs to the data team
0h
hours saved per product review
0
shared view for product + leadership
The challenge
Why Product and Growth teams need a better way
Product KPIs live in one tool while account or revenue context lives elsewhere
Connect warehouse, event tools, and billing in one workspace
Teams keep rebuilding the same adoption and retention views for reviews
Save KPI dashboards once and reuse them every review cycle
Follow-up questions often require a data team handoff
Keep asking follow-up questions in the same conversation — no handoffs
How it works
Four steps from question to dashboard
Connect warehouse, app databases, event tools, and revenue sources
Ask product questions in plain English and validate the returned steps
Save KPI dashboards for weekly product and leadership reviews
Set watches on activation, retention, and account health changes
What it looks like
See Spark in action
Retention by Cohort
Ask product questions across data sources
Connect your warehouse, app databases, and event tools. Ask "What changed in activation this week?" naturally.
WAU
12.4K
+9.6%
Activation
68%
+4.2pp
Trend
Save KPI dashboards
Pin the activation, WAU, retention, and expansion view. Share it in the weekly product review.
Activation rate below 65% target
Triggered 2h ago — 63% for new cohort
D30 retention above 80%
Last checked 15m ago — 82%
Feature adoption shifting post-release
Watch product health signals
Set watches on activation rates, retention by cohort, or feature adoption changes.
Insight: April cohort shows 86% D30 retention, highest since launch. Onboarding flow changes drove +4pp.
Cohort and adoption charts
Spark generates retention curves, feature adoption timelines, and segment comparison charts.
Start free — no credit card, no setup call.
Integrations
Connect the tools you already use
Spark connects to databases, SaaS platforms, spreadsheets, and files. Use them all together in the same workspace.
What teams say
Real results from real teams
Product reviews used to start with "can someone pull the latest numbers?" Now the dashboard is always ready.
Maya Singh
Product Lead at Lattice Labs
We connected our warehouse with Stripe and finally saw how usage patterns drive expansion revenue.
Chris Langford
Growth PM at Arcline SaaS
Why Spark
Spark vs. traditional approach
Product + revenue data together
Warehouse, events, billing in one query
Different tools, different teams
KPI dashboards
Save from any conversation
Request from data/analytics team
Retention and cohort analysis
Ask in plain English
Write complex SQL or use specialized tools
Health watches
Automatic threshold monitoring
Manual checks before each review
Share across teams
Link or embed, no re-run needed
Copy charts to slides
Security and trust
Your data stays private and protected
Spark is designed for teams that care about data security. Credentials are encrypted, access is scoped, and shared views never expose raw connection details.
AES-256-GCM encryption
All connection credentials are encrypted at rest using AES-256-GCM with per-record initialization vectors.
Role-based access
Workspace members see only the connections, documents, and dashboards their role allows.
Password-protected links
Shared dashboards and public links can require a password before anyone views the data.
Query transparency
Every AI-generated query is visible and inspectable. Nothing runs without your data sources approving the connection.
Team-scoped workspaces
Each workspace is isolated. Data sources, documents, and dashboards never leak across teams.
Allowed-domain embeds
Embedded dashboards only render on domains you explicitly allow. No unauthorized embedding.
FAQ
Common questions about product workflows
Answers to the questions teams ask when evaluating whether Spark is the right fit for this workflow.
Related use cases
More ways teams use Spark
Ready to connect product data to business outcomes?
Connect your warehouse, event tools, and revenue sources. Ask the first product question and save the answer as a reusable dashboard.