Put an AI agent to work on your Supabase data
Connect Supabase in one click and delegate the data busywork: an autonomous agent that reads your Postgres tables, watches for new rows, runs hygiene checks, answers support questions from your records, and files reports — always within the row-level security you grant. You set the autonomy, it does the work.
7-day trial · Cancel anytime
Fleece AI connects to Supabase through managed OAuth and lets autonomous agents query your Postgres tables, read rows, look up auth users, and react to new records in real time — always within the row-level security and permissions you grant. Agents combine Supabase with 3,000+ apps like Slack, Google Sheets, and Notion, so a new row can become a digest, a data-hygiene check, a support answer, or a report.
At a glance
| Category | Database |
|---|---|
| Availability | Pro plan and up — included in the 7-day trial |
| Connects to | 3,000+ apps via managed OAuth |
| Setup | Connect your tools — no code required |
| Autonomy | Suggest-only to fully autonomous, with approval gates |
| Pricing | 7-day trial (€1 card check, credited back), then paid plans |
By Loïc Jané · Updated June 15, 2026
What a Fleece agent does with Supabase
Supabase is the Postgres backend under your product — the tables and rows that hold your users, the auth users and sessions behind sign-in, the storage buckets holding uploads, the edge functions running your server logic, and the realtime subscriptions that stream changes to your app. That data is where the signal lives: a spike in signups, an order that never got fulfilled, an account asking for help. A Fleece agent sits on top of that database and turns those signals into action, without you writing another cron job or webhook handler.
Under the hood, the connection runs through managed OAuth — you authorize Supabase once, and Fleece stores, scopes, and refreshes tokens securely; you never paste a service-role key into a script. The agent can query tables, read and filter rows, look up auth users, inspect storage buckets, and follow relationships across your schema. It works strictly within the access you grant: row-level security stays enforced, the agent sees only what its connection is permitted to see, and it never bypasses your policies. Realtime and new-row triggers let it react the moment a record is inserted or changed, so a fresh signup or a new order is handled in seconds rather than on a nightly batch.
What makes this different from a hand-written edge function or a stack of database webhooks is judgment. A trigger fires the same way every time; an agent reads the actual rows, decides whether the pattern matters, drafts a plain-language summary, and coordinates other tools to finish the job. And because Fleece agents work as a hierarchy — a lead agent delegating to specialized child agents — one Supabase-facing agent can hand a summary to a reporting agent, a Slack agent, or a support agent and report the result back, all under the approval rules you set.
What the agent can do in Supabase
Query tables and rows
Reads and filters rows across your Postgres tables, follows foreign-key relationships, and looks up auth users to answer a question or build a summary.
React to new rows
Fires on realtime and insert triggers the moment a signup, order, or event row lands — no nightly batch, no polling loop to maintain.
Data-hygiene checks
Scans for orphaned rows, missing foreign keys, duplicates, and anomalies, then flags what it finds for your approval before anything is changed.
Support context lookup
Reads a customer's records — plan, usage, recent activity — so it can answer a ticket accurately instead of asking the user to repeat themselves.
Reporting pipelines
Runs aggregate queries and files the numbers as a plain-language brief or a live sheet, on a schedule you set, without a data engineer in the loop.
Works within your policies
Operates strictly inside the row-level security and permissions you grant; sensitive writes pause for your one-click approval before they run.
Automations teams run on Supabase
These are concrete setups you can describe to a Fleece agent in plain language. Each one combines Supabase with other connected apps.
Growth: turn new rows into a signup digest
The agent watches your auth users and signups table through realtime triggers and, each morning, posts a digest to Slack: how many new accounts, which plan, where they came from, and any that look like duplicates or test data. Instead of eyeballing the table in the Supabase dashboard, the team reads a plain-language summary in the channel they already live in.
Data quality: catch anomalies before they spread
On a schedule, the agent runs hygiene queries across your tables — orphaned rows, null foreign keys, subscriptions with no matching customer, values outside expected ranges — and writes each finding to a Notion database with the row IDs and a suggested fix. Nothing is deleted or updated automatically: destructive changes pause for your one-click approval, so a false positive never quietly corrupts production data.
Support: answer tickets with the real record
When a question lands in your Slack #support channel, the agent looks up that customer in Supabase — their plan, recent orders, last activity, storage usage — and drafts an accurate reply grounded in the actual row, within the row-level security you granted. If it turns out to be a real bug rather than a question, it files a GitHub issue with the relevant IDs attached and links it back in the thread.
Reporting: a weekly metrics sheet that fills itself
Every Monday the agent runs aggregate queries over your Postgres tables — active users, revenue, churn, feature adoption — and appends the results to a Google Sheets tab, then posts a short plain-language readout of what moved and why. The recurring export that used to be a manual SQL-and-copy chore now arrives before anyone opens their laptop.
How to connect Supabase to Fleece AI
Create your Fleece account
Sign up and start the 7-day trial. You land in a workspace where agents, flows, and integrations live together.
Connect Supabase via managed OAuth
Pick Supabase from the integrations catalog and authorize it in one click. Fleece manages tokens and scopes for you; you can revoke access at any time from Supabase or from Fleece.
Describe the job in plain language
Create an agent and tell it what to watch and what to do — "every morning, summarize new signups from the users table and post the digest to #growth". No SQL scripting or webhook wiring required.
Set autonomy and approval gates
Choose what the agent may do on its own and what waits for your sign-off. Any write or destructive change pauses for one-click approval.
Run it on triggers or a schedule
Let the agent react to new rows in real time, or schedule recurring flows — morning digests, weekly hygiene sweeps, Monday reports — that run without you.
Supabase works better with the rest of your stack
Supabase automations get powerful when they cross app boundaries. Pair Supabase with Slack to turn new rows into channel digests, with Notion to log data-quality findings, with GitHub to file bugs surfaced in your records, or with Google Sheets to keep a live metrics report — all through the same agent, all under the same approval rules and within the row-level security you grant. Fleece connects to 3,000+ apps, so the stack you already use is almost certainly covered.
Frequently asked questions
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Put your Supabase data on autopilot
Connect Supabase in one click, describe the job in plain language, and let an autonomous agent read, watch, and report — within the access you grant. 7-day trial, cancel anytime.
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