Trusted by 60 enterprise users

The governance layer
for AI on production data.

DataBull is the secure layer that engineering teams use to let agents query your real data without exposing PII or confidential data.

Book a demo See how it works
Row-level permissions Bring your own cloud
app.databull.ai
12 sources live
Support agent · scoped to tenant_id 4421
Show me failed payments for this customer in the last 7 days.
DB

Found 3 failed payments for this account. Name, email, and card number masked. Query scoped to tenant_id 4421 only.

card_declined
2 events
insufficient_funds
1 event
audit logged
✓
Agent will only see rows it has access to...
Connected sources
S
Salesforce CRM
Live
Pg
PostgreSQL
Live
G
Google Analytics
Live
St
Stripe
Live
H
HubSpot
Syncing...
Add a source
60
enterprise reps using daily
500+
data connectors
Row
level access control
BYOC
bring your own cloud
01 Unified data and access-control plane

One layer between your agents and your data.

Connect your databases, warehouses, and SaaS tools once. DataBull handles schema understanding, permission resolution, and natural-language query translation, so any LLM or agent can read business data safely.

See all features

Schema understanding

DataBull introspects your Postgres, Snowflake, Stripe, and CRM schemas so agents know exactly what they can query.

Natural language to SQL

Translate plain-English questions into safe, scoped queries against your connected sources. No raw SQL exposure.

Audit logging

Every query, by every agent, logged and searchable. Know exactly what your AI is doing with your production data.

No raw credentials

Agents connect through DataBull, not directly to your databases. Rotate, scope, and revoke access without re-deploying.

Agent layer Support agent Customer service AI In-product copilot Per-user permissions Internal tools Team copilots user_id + query DataBull control plane Resolve scope Schema + permissions per user Row-level access enforced per query Generate SQL Natural language translated to SQL Tenant filter and read-only enforced Mask + return PII stripped before leaving DataBull Name · email · card all masked Your data Postgres Snowflake Stripe HubSpot, Salesforce + 500 more sources Audit trail Logged at every step. user_id · query · intent · scope · generated_sql · rows_returned · pii_masked · latency · timestamp Every agent query is fully auditable. Every row returned. Every PII field that was masked.
02 Built for agents and AI-native teams
Customer support agent · scoped to one account
Agent reads only this customer's tickets, orders, and billing. Never another tenant's data.
In-product chat · per-user permissions
Each end user's session inherits their role-based access. Same agent, different rows.
Internal copilot · across Postgres + Stripe + CRM
One connection point. PII masked before it ever reaches the LLM. Every query audit logged.

Any LLM. Any agent. Safely connected.

Point your agents at DataBull and they get governed access to every connected source. No raw credentials in your prompts. No risk of an agent reading data it shouldn't.

Works with any LLM or agent framework
Row-level permissions enforced on every query
Read-only by default. No destructive queries
Full audit trail of every query and response
03 Governance built in

The bottleneck isn't queries. It's governance.

Most attempts to put AI on production data fail at the same place: agents need raw credentials, there's no row-level access control, and no safe way to let an LLM query without risking a leak. DataBull solves that.

PII masking

Detect and redact personally identifiable information before it ever reaches an LLM or agent.

Row-level permissions

Scope every agent and every user to only the rows they're authorized to see. Enforced at the query layer.

Read-only by default

Agents can't drop tables or modify rows. Destructive queries are blocked at the control plane.

On-prem deployment

Deploy DataBull inside your own VPC for full data sovereignty, compliance, and control.

04 Who we built it for

For teams putting AI on production data.

Every team building agents on real customer data hits the same wall. Permissions, credentials, and audit logging slow everything down. DataBull is the layer that makes it safe to ship.

Customer support agents
Let support AI read tickets, orders, and account history, scoped to one customer at a time.
In-product copilots
Ship chat experiences that answer with each user's own data, with their permissions.
Internal AI tools
Give your team a copilot that reads across Postgres, Stripe, and your CRM without leaking data.
Retail and e-commerce
AI on usage, support, and order data, without exposing PII or credentials to the model.
Banking and financial services
Strict row-level access and full audit trail for every agent query against production data.
B2B SaaS
Multi-tenant by design. Agents can only ever see data for the tenant they're scoped to.
05 Integrations

Connect everything. Govern it once.

Postgres, Snowflake, Stripe, CRMs, and 500+ more. Connect each source once and DataBull handles permissions, masking, and audit logging across all of them.

Salesforce HubSpot PostgreSQL MySQL Snowflake BigQuery Google Drive Stripe Shopify Slack Jira GitHub Meta Ads Google Ads Mixpanel Segment Intercom Zendesk MCP Servers REST APIs AWS S3 MongoDB Airtable Webhooks +480 more
06 How it fits in your stack

Drop in between your agents and your data.

Your existing LLM, your existing agent framework, your existing databases. DataBull is the layer in between. No rewrites, no rip-and-replace.

Any LLM
MCP servers
REST API
SDKs
Webhooks

Ship AI on production data without losing sleep.

Used daily by 60 enterprise reps across retail, ecommerce, and banking. See it run on a live source on the call.

Book a demo See how it works

30 minutes. We'll connect to a real source live.