DataGPT
Lets anyone on a business team ask a plain-English question about company data — like 'why did sales drop last week?' — and get a real, sourced answer without writing a line of SQL.
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Description
In most companies, a business question about the data — "why did signups drop in March?" — turns into a Slack message to an analyst, who writes a SQL query, builds a chart, and gets back to you a day or two later. DataGPT is built to remove that middleman: it's a conversational AI data analyst that lets anyone type a question in plain language and get an instant, analyst-grade answer, complete with the reasoning and comparisons that led to it.
DataGPT connects to a company's databases (including MySQL, Oracle, and big-data sources) and, when asked a question, plans an approach, executes meaningful comparisons and deep-dives, and curates the result into an actual analysis rather than a raw number. Beyond reactive Q&A, it proactively surfaces daily summaries and anomaly alerts, offers drill-down exploration and metric comparisons, and includes role-based access controls for enterprise governance. Founded in 2023 by Arina Curtis, Darren Pegg and Sasha MacKinnon, and headquartered in San Francisco with a Montreal presence, the company has raised $10-11.9M and is pursuing a Series A. Pricing starts around $1,750/month for 10 users, or from $99/month per team on lighter plans, with no free trial — engagement begins with a paid pilot program.
💬 Our review
The short version: DataGPT is built for a mid-size-to-enterprise company that has real data infrastructure and an analyst bottleneck, not a small startup wanting a free chat-with-my-spreadsheet tool.
The proactive layer — daily summaries and anomaly alerts pushed to you, rather than only answering questions you think to ask — is the more interesting part of the pitch versus a plain "chat with your database" tool, since it can surface a problem before anyone notices it manually. The claimed 15x cost reduction on 1TB dataset processing and 2,178% average quarterly ROI are vendor-reported figures worth verifying against your own workload rather than taking at face value. The honest caveat: at roughly $1,750+/month with no free trial and a paid-pilot-only onboarding, this is a genuine budget commitment aimed squarely at companies that already have the data volume and analyst pain to justify it — a small team curious about the category should look at a cheaper, self-serve tool like Julius AI first, and only move to DataGPT once you've confirmed the ROI case internally.
💰 Pricing
📊 Global score
🤖 AI-enriched data
À partir d'environ $1 750/mois pour 10 utilisateurs ; plans plus légers dès $99/mois par équipe. Aucun essai gratuit, démarrage via un pilote payant.
Pros
Réponses en langage naturel sans SQL, avec raisonnement et comparaisons
Alertes proactives et résumés quotidiens, pas seulement réactif
Connexion à des sources de données d'entreprise (MySQL, Oracle, big data)
Contrôles d'accès par rôle pour la gouvernance entreprise
Cons
Aucun essai gratuit, engagement direct via pilote payant coûteux
Prix élevé (~$1 750/mois pour 10 utilisateurs), inadapté aux petites équipes
Chiffres de ROI et d'économies fournis par le vendeur, à vérifier soi-même