
Turn data chaos to business clarity
Point Sigma is an AI-driven analytics platform that connects to your data sources, discovers data types and joins automatically, then surfaces statistically relevant patterns as a scrollable feed of charts. Its "Artificial Curiosity" engine explores datasets on its own to generate insights and questions, so teams get analysis without the usual manual cleaning, modelling, and transformation work. Built by a small London team for businesses that want analytics output without hiring a data team.
An AI engine autonomously explores your datasets to find statistically significant patterns and relationships, generating insights and follow-up questions you did not ask for.
Connect databases, SaaS apps, and spreadsheets in seconds. Integrations include PostgreSQL, MySQL, HubSpot, Salesforce, Zoho CRM, Airtable, Google Sheets, Google Analytics, Google Ads, Zendesk, Mailchimp, and Excel.
The platform infers column data types and detects relationships across tables and systems, building a unified view without manual data modelling.
Ask questions of your data in plain language and get answers back as charts you can customize, plus suggested related questions to explore next.
Instead of building charts from scratch, browse a feed of generated visualizations, then upvote or downvote patterns to steer what the engine surfaces.
Save discovered patterns into folders and dashboards, edit graph types, axes, and filters, and share them with stakeholders for reporting.
Get analyst-grade pattern discovery and dashboards without hiring data engineers or building a warehouse first.
Pull scattered client data from CRM, ads, and analytics tools into one view and produce insight-led reports faster.
Use the Custom plan's embedded components, API access, and whitelabeling to ship analytics inside your own SaaS product.
Navigate large, messy datasets to spot anomalies and hidden relationships during audits or data quality reviews.
Track where data came from, review automated metadata discovery, and manually manage data types, joins, paths, and filters when you need control.
Set refresh schedules, load data on demand, and apply data processing restrictions. Refresh frequency is hourly on Explore and on-demand on Discover.
The Custom plan adds embedded components, API access, custom branding, and whitelabeling for software companies putting analytics inside their own product.
Production-oriented controls for serving multiple customers or business units from one deployment with data separated at the row level.
Let the engine surface which segments, channels, and behaviours actually correlate with revenue instead of hand-building funnel reports.

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