Know more.
Spend less. Stay safe.
Replace your data team, your warehouse, and your BI stack with one autonomous platform. Connect a source, ask a question, get an answer in minutes, not months.
Know more. Spend less. Stay safe.
Decision-ready data without the cost or complexity of a traditional team.
Know your numbers and hit your targets without hiring a data team.
From first connection to clear answers-no waiting on reports or engineers.
Reduce blind spots. Your data in one place so your decisions are based on reality.
Audit-ready and secure so you can focus on the business.
Everything between your data
and your question. Automated.
Not a chatbot bolted onto your warehouse. The warehouse, the pipelines, the semantic layer, and the conversational UX: built and operated as one system.
One platform replaces five.
No Snowflake to provision. No Fivetran subscription. No Airflow to babysit. DataAgents runs the warehouse, the loaders, the orchestrator, and the lineage. Included.
DataAgentsEvery metric defined once.
Two people, two phrasings, one answer. Revenue is revenue across Slack, the web app, email, and the API. The agents enforce it; the team trusts it.
revenue=SUM(charge.net) WHERE refunded = 0arr=SUM(subscription.mrr) × 12net_churn=(churned − expansion) / starting_arrSelf-healing. Self-watching.
Schema drifted at 03:14? Patched and replayed by 03:16. Anomaly in EU revenue? Flagged in #alerts before standup. The platform runs when no one is watching.
All your tools and data in one place.
Connect CRM, databases, and apps in minutes — no engineering project required. Just authenticate and DataAgents auto-maps your schema.
Web appWeb appOne agent. Six places to ask.
Same memory, same metrics, same answer, whether your CFO emails on Saturday or a sales rep DMs the bot from a customer site.
POST /v1/ask
{ "q": "top 5 by ARR" }
→ [
{ "name":"Acme", "arr":482000 },
{ "name":"Globex","arr":391000 },
…
]Web appprimaryThe questions you'd ask a senior analyst.
Answered in 12 seconds.
Pick a question. DataAgents pulls from the right gold tables, runs the join, builds the chart, writes the explanation, then sends it wherever your team works.
metrics, already cleaned, joined, and governed.
Find out something broke
before your customers do.
The same agents that build your gold tables also watch them. Every governed metric is monitored, every drift is investigated, every alert lands with the cause and the fix.
Detects anomalies, not just thresholds
Learns the seasonal shape of every governed metric. Flags real deviations, not noise. No alert fatigue.
Finds the cause across your sources
Cross-checks Stripe, HubSpot, GA4, and your CRM to pinpoint where the break started.
One click to act
Page on-call, open a ticket, apply a patch, snooze. Every alert ends with the actions that matter.
Three people. Three ways to ask.
One answer.
Most "AI for data" tools text-to-SQL their way to a dashboard and pray the joins are right. The DataAgents semantic layer is the product. It is built from your sources and governed forever. Same definition, every team, every channel.
MRR = Σ active subscription monthly valueexcludes one-time · excludes refunds · grain: month
What a data team costs
vs. what you'd pay us.
Drag the sliders. The math updates live. Most teams land between 80% and 95% savings, and ship the first answer the same week.
Estimate includes loaded salaries + standard tooling (warehouse, BI, orchestration, ML infra). Real costs vary; we'll send a personalized report after a 20-minute call.
How we stack up against the alternatives.
The real choice isn't "which AI tool talks to my warehouse." It's whether you need a warehouse, a pipeline team, and a BI stack at all.
¹ ChatGPT/Claude are fast on the CSV you paste. They can't ingest your sources, don't know your metrics, can't forecast, and won't watch your business overnight.
Frequently asked,
frequently answered.
Everything we get asked in demos. Don't see yours? Email us. A human replies, usually the same day.
Connect a source.
Get an answer today.
Five minutes to plug in. The platform builds the warehouse, the pipelines, and the semantic layer for you. The first useful answer lands before lunch.