Ask Claude or ChatGPT about the data your company keeps in BigQuery, and get answers from the tables each team is approved to see.
Read from BigQuery when someone asks. Nothing exported, nothing copied, and changes only where you allow them.
BigQuery Data & warehouses 
FrontierOps Permissions, definitions, record 
Any AI The AI your team uses Which campaigns brought in the most new customers last month, and what did each one cost?
How did weekly active users change over the last eight weeks, by plan?
Add next quarter’s sales targets for each region to the targets table.
Insert, update and delete are three separate permissions, never on the User role. An admin decides which roles get each one. Every write is on record.
Already on dbt? We import the project (dbt Core is enough), and its definitions guide every answer from BigQuery.
BigQuery holds the data, but getting an answer out of it still means finding someone who writes SQL. FrontierOps lets anyone ask in plain English: each team sees only its approved tables, your definitions guide the answer, and every query is checked before it runs, so the number marketing sees is the one finance reports.
An admin connects BigQuery one time. Nobody hands over a personal login.
Each answer is read at the moment of the question. Nothing is exported or copied, so there is nothing to keep in sync.
What each role can see and do holds in every AI your team uses, and in your own agents.
Every question and every action, by every person and agent, in one audit trail.
No. It sees the tables you approve, named by project, dataset and table, and each team can get its own set. A query that names anything else, or tries to look up the schema, is refused before BigQuery runs it.
Keep them for your data team. FrontierOps is for everyone else: people who never open the Google Cloud console, each team limited to its approved tables, every question on record, and your CRM, billing and support desk next to the warehouse under the same permissions.
It cannot export: EXPORT DATA, LOAD DATA, scripts and procedure calls are refused, one statement per call. It can insert, update or delete rows in approved tables only if you turn that on for a role, and every statement is on record.
Yes, and one built for a whole company. FrontierOps gives Claude, ChatGPT and any other MCP client one connection to BigQuery, set up once by an admin. What each role can read or change is decided in FrontierOps, and every call is on record, instead of each person running their own server with their own login.
A direct connection links one AI to BigQuery through one person’s login, with that person’s settings. That works for one person. For a team it means no shared definitions, no single place to decide who can see or change what, and starting over when you switch AI. Through FrontierOps, BigQuery is connected once, for every AI and every agent, under one set of permissions, with every call on record.
Google Sheets Paste a link and Claude or ChatGPT reads your Google Sheets, adds rows to your logs and fills in the cells you ask for. Connect Google Sheets to any AI 
HubSpot Ask Claude or ChatGPT about your contacts, companies and their activity in HubSpot, and have the follow-up logged in the CRM. Connect HubSpot to any AI 
Stripe Ask Claude or ChatGPT what renews, what is overdue, which payments failed and what made up each payout in Stripe. Connect Stripe to any AI