Fewer one off requests
Common questions are answered without a new ticket.
AI agents for Data
Turn questions into reports.
Agents pull the numbers, build the report and share it on schedule, inside the data access you allow.
Answers on time, from data you trust.
Reports that run themselves
Recurring reports are built and shared on schedule.
Access under control
Agents only query the sources they are allowed to use.
Answers to data questions
Teams ask in Slack or the workspace, and the agent answers from approved sources with the query and sources attached.
- 09:41 Request classified
- 09:43 Scope checked
- 09:48 Evidence gathered
- 10:02 Approval waiting
Artifacts Contract delta.pdf Spend summary.csv Recommendation.md
Dashboards kept current
Agents refresh the numbers and flag anything that moved more than expected.
184 Runs
37m Turnaround
92% Approval clarity
$428 Model cost
Reports on schedule
Weekly and monthly reports are built and shared in the channels people read.
Mon Tue Wed Thu Fri
Daily Executive brief
Runs, pauses for review when needed, and ships an artifact.
Weekly Pipeline review
Runs, pauses for review when needed, and ships an artifact.
Event Renewal risk alert
Runs, pauses for review when needed, and ships an artifact.
Governed data access
Model rules and the AI gateway control which sources and models each agent can use, and every query is logged.
- Renewal analyst Policy passed Advanced model
- Ticket triage Policy passed Fast model
- HR assistant Blocked by policy No call made
Template library
Start from a Data template.
Ready made workflows for Data teams. Each one comes with its steps, an agent setup, approval rules and the skills it needs.
- Data template
Weekly metrics report
- Workflow steps
- Agent setup
- Approval rules
- Skills
A person approves: new metric definitions
- Data template
Data question answers
- Workflow steps
- Agent setup
- Approval rules
- Skills
A person approves: new data sources
- Data template
Dashboard refresh and anomaly flag
- Workflow steps
- Agent setup
- Approval rules
- Skills
A person approves: external sharing
Getting started
How Data teams get started.
-
Pick one workflow
Start with a real data workflow that repeats every week.
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Connect your tools
Agents work inside PostgreSQL, Google Drive, Slack and your BI tools.
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Set the rules
Choose what the agent may do alone and what waits for a person.
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Start with review
A person checks the work at first. Give the agent more room as it earns trust.
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Expand what works
Add the next workflow, or bring the same setup to another team.
Every feature runs inside the same six controls.
Identity, access, approvals, supervision, audit and policy apply to every agent and every run, whichever part of the workspace it happens in.
See governance and audit- Identity
- Access
- Approvals
- Supervision
- Audit
- Policy
Built for every team
FAQ
AI agents for Data: questions and answers
Short answers to what data teams ask before they start.
Contact us directlyCan the agent see all our data?
No. It only uses the sources you approve for that agent, and every query is logged.
How do we know an answer is right?
Each answer shows the query and sources behind it in the run trace, so it can be checked.
What always stays with a person?
Metric definitions, new data sources and anything published outside the company. You can add more rules at any time.
Which tools does it work with?
Common tools for data teams include PostgreSQL, Google Drive, Slack and your BI tools. Ask us about the tools your team uses.
Do we need engineers to set this up?
No. During early access we configure and deploy your first workflows directly with your team.
The multiplayer workspace for humans and AI agents is how teams move beyond prompting and safely hand AI real work. It gives people one place to plan, approve, and oversee execution, so they can run work with AI agents they can govern and trust.