Govern Every Query.
Before It Ever Runs.
Every query is filtered by row and by role. SQLShield lets nothing through but SELECT. The metadata layer shows AI agents clean, public names, never your real tables or columns. Governance, built into the query layer itself.
Policies enforced the same way across every database
The Governance Gap
Most AI-database integrations skip governance entirely, connecting agents straight to production schemas with no policy layer in between.
Unrestricted AI Access
AI agents connect directly to raw schemas, seeing every table and column, including the sensitive ones no one meant to expose.
Inconsistent Permissions
Role and department access rules live in spreadsheets and tribal knowledge, not enforced at the query layer where it actually matters.
Unchecked Destructive Queries
Without statement-level validation, a single AI-generated DROP, DELETE, or ALTER can reach production with nothing standing in its way.
How Governance Works
From policy definition to token-level tracking, in four steps enforced automatically at the query layer.
Define policies
Set row-level filters, column visibility, and role-based access per datasource, once, at the source.
Enforce automatically
Every query is parsed into an AST and validated by SQLShield before it ever touches your database.
Scope every credential
Issue expiring, org- and user-bound tokens instead of shared passwords or standing database access.
Track token usage
Every credential's activity is tracked per token, so you know which agent touched which datasource, and when.
Everything Governance Needs, Built In
A complete toolkit for enforcing policy at the query layer, not after the fact, without ever altering your actual data.
Row-Level Security
SQL-based filters, like department_id = 5, are rewritten into every executed query as part of SQLShield's transformation step.
Privacy Controls
Sensitive tables and columns stay hidden from the LLM's context window until explicitly exposed to specific roles.
SQLShield
Parses every query into an AST with sqlglot, blocking INSERT, UPDATE, DELETE, DROP, ALTER, GRANT, and TRUNCATE, and auto-appending a LIMIT clause to cap result size.
Scoped Access Tokens
Tokens are bound to an org and a user, can be restricted to a single datasource, set to auto-expire, and have their usage tracked individually.
Semantic Metadata
The AI agent only ever sees clean business names, like Customers, never the real physical name behind it, like t_users_v2_fnl. Your actual schema stays hidden from every query.
Split MCP Architecture
A read-only Query server for AI agents, and a separate Admin server for write operations that keep humans in the loop.
The difference it makes
Without a Governance Layer
Unfiltered Table Access
AI agents query the full schema directly, with no row or column-level restriction based on who's asking.
Same Access for Every Role
Every user and agent sees the same tables and columns, regardless of team, department, or seniority.
Shared, Long-Lived Credentials
One database password gets reused across scripts, agents, and teams, with no expiry and no clear owner.
Undocumented Sensitive Columns
PII and financial fields sit unlabeled next to everything else, one prompt away from being surfaced.
With TernoDBI
Row-Level Security
Access filters are enforced automatically at the query layer, before a single row is returned.
Role-Based Filters
What a user or agent can see depends on their role, so access scales with the org instead of staying all-or-nothing.
Scoped, Expiring Tokens
Every credential is bound to an org and a user, with an expiration date and an optional datasource scope.
Privacy-by-Default Masking
Sensitive tables and columns are hidden from the LLM's context window unless a role explicitly grants access.
Built for Trust, Not Guesswork
Policy enforced at the source means access decisions never depend on an agent remembering the rules.
Policy-aware enforcement
Row-level filters and column masks are applied as part of SQLShield's query transformation step, before a query reaches your database.
Segregated Admin Access
Renaming a table or editing metadata runs through a separate Admin server, kept apart from the read-only Query server your agents use.
Least-privilege by design
TernoDBI is meant to run against a read-only database user. It never needs write access to your actual warehouse to answer a question.
Built for Enterprise Confidence
Self-Hosted
Deploy inside your own cloud or on-premise. No external dependencies. Your infrastructure, your rules.
Data Shared
We never access, store, or train on your data. Your schemas and queries stay entirely within your control.
Contact Us
Have a question, need a demo, or want to work with us? Reach out and our team will get back to you shortly.
Get in touch
We’re here to help you with data insights, onboarding, pricing or anything else.
reachus@terno.ai
Phone
+1 (412) 568-3901
Address
9450, SW Gemini Dr, PMB 90168, Beaverton, Oregon 97008-7105, United States