Point Sigma

Turn data chaos to business clarity

AI Data & Analytics Business Intelligence www.point-sigma.com

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Founded

2019

Starting Price

£20

About Point Sigma

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.

Pros & Cons

Pros

Removes the data prep bottleneck: connects, types, and joins raw data automatically instead of requiring a clean warehouse first
Artificial Curiosity surfaces patterns you would not have thought to query, which is genuinely different from dashboard-first BI tools
Fast time to first insight, with customers reporting useful output within minutes of uploading data
Large connector library (500+ claimed) covering CRMs, ad platforms, spreadsheets, and SQL databases
Natural language search returns customizable charts plus suggested follow-up questions
Custom plan offers embedded components, API access, and whitelabeling for software companies reselling analytics

Cons

Very large jumps between tiers: £20 to £100 to £1,000 per user per month, with per-user billing that scales badly across a wide rollout
Tight data ceilings even at the top standard tier: 50 tables and 1 GB storage on the £1,000 Discover plan
The £20 View plan cannot connect data or run discovery at all, so at least one Explore or Discover seat is mandatory
Almost no independent review footprint (a single verified review on GetApp), so third-party validation is thin
Small company (roughly 6 employees, about $1.09M raised), which is a vendor-risk consideration for critical reporting
Connector count is stated inconsistently across the site (350+ on some pages, 500+ on the homepage)
One customer noted natural language search was quite constrained early in their contract, though later releases improved it

Key Features

Artificial Curiosity pattern discovery

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.

500+ pre-built connectors

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.

Automatic join and data type discovery

The platform infers column data types and detects relationships across tables and systems, building a unified view without manual data modelling.

Natural language search

Ask questions of your data in plain language and get answers back as charts you can customize, plus suggested related questions to explore next.

Auto-generated graph feed

Instead of building charts from scratch, browse a feed of generated visualizations, then upvote or downvote patterns to steer what the engine surfaces.

Dashboards and folders

Save discovered patterns into folders and dashboards, edit graph types, axes, and filters, and share them with stakeholders for reporting.

Data lineage and metadata management

Track where data came from, review automated metadata discovery, and manually manage data types, joins, paths, and filters when you need control.

Scheduled and on-demand data refresh

Set refresh schedules, load data on demand, and apply data processing restrictions. Refresh frequency is hourly on Explore and on-demand on Discover.

Embedded analytics and API access

The Custom plan adds embedded components, API access, custom branding, and whitelabeling for software companies putting analytics inside their own product.