◆AI Copilot · Observability · Safety · in one workbench

Understand your database.
Investigate issues.
Act with confidence.

Quorum is the AI-native database workbench that helps developers and data teams query complex systems, trace data problems, observe live database health, and take the next safe action — across SQL Server, PostgreSQL, MySQL, and MongoDB.

Contact→See how it works →Talk to the team · hands-on walkthrough · early access

Quorum — warehouse-prod⌘K to search · ⌘N new query

Tuesday · 14:32

Good afternoon, Piyush.

Action Center● 1 critical2 high

Session 87 is blocking 14 queries on public.orders

UPDATE orders · 8m 24s · 3 checkout writes waiting

checkout-write pattern regressed 6.4× in 90 min

p95 84ms → 540ms · plan flipped to seq scan

Missing composite index on orders(status, created_at)

39,210 scans today · 23× read benefit

Trusted by teams shipping onPostgreSQLSQL ServerMySQLMongoDBDuckDBSnowflakeBigQuery

A new shape of workbench

Not just another database client.

Traditional clients give you a tree, an editor, and a result grid — then leave the rest to memory, scripts, and a ticket to the DBA. Quorum compresses the whole workflow into one place: explore, query, understand, investigate, observe, diagnose, act.

What you need to do

Traditional clients

Quorum

Find where data lives

Tree-navigate, grep, guess

Ask AI: "where is order status stored?"

Generate queries

Write by hand · paste from elsewhere

Natural language → dialect-aware SQL or Mongo

Debug broken data flows

Trial-and-error, separate scripts

Guided investigation with stepwise queries

Monitor live health

Switch to Datadog / Grafana

In-workbench, with the action one click away

Kill a blocker / find an index

Page the DBA

Inline, with a confirmation modal and audit trail

◆AI Copilot

Ask your database better questions.

Schema-aware, dialect-aware, and embedded in the editor — not bolted on as a chat window. Quorum's Copilot uses your actual schema and recent query history to generate SQL, explain plans, fix errors, and prepare safe writes.

◆QueryFind orders stuck in fulfillment > 15minhaiku-4.5 · 1.4s

Joining orders → event_outbox → fulfillment.shipments via LEFT JOINs surfaces which step is missing for stuck orders.

-- generated · stuck.sql
SELECT s.id, s.status, s.created_at,
       eo.id AS event_id,
       f.id  AS fulfillment_id
FROM orders s
LEFT JOIN event_outbox eo
  ON eo.aggregate_id = s.id::text
LEFT JOIN fulfillment.shipments f
  ON f.order_id = s.id
WHERE s.status = 'PENDING_FULFILLMENT'
  AND s.created_at < NOW() - INTERVAL '15 minutes'
ORDER BY s.created_at ASC
LIMIT 1000;

Insert Run preview

◆

Schema-aware in real time

The Copilot reads your active connection's schema tree before every prompt. No glue scripts, no copy-pasted DDL.

◆

Plain-language explanations

Pin a query, ask why it's slow, get a structured plan walkthrough with the bottleneck called out.

◆

Dialect-aware generation

Quorum knows whether to emit T-SQL, PL/pgSQL, MySQL, or Mongo aggregation pipelines based on the active connection.

◆

Per-connection AI notes

Add house rules: "order ids are bigint", "never query outbox without published_at filter".

◆

Error → fix in one card

When a query fails, the error card surfaces the likely cause and a corrected version inline. One click to apply.

◇Investigation mode

Trace the problem, not just the syntax.

When a record goes missing, a sync silently fails, or a customer's order is stuck — Quorum turns the question into a guided diagnostic timeline. Each step is a hypothesis, a read-only query, a result, and a verdict.

Generated stepwise queries — never destructive
Confirmed / no-match / needs review state per step
Root-cause summary distinguishes fact from inference
Save the whole case as a reusable playbook

Investigation · in progress

Why is order #82147 missing downstream?

1ConfirmedOrder exists in source

2ConfirmedOutbox event was created

3ConfirmedIntegration job processed event

4No matchDownstream shipment record

5RunningCompare against neighbors

6Not runPull fulfillment-service logs

Likely cause

The break sits between the integration job and target persistence. Fulfillment-service likely rolled back silently or marked the event done early. Same break point as case #79221 on Apr 28.

◉Observability

See what your database is doing.
Understand why. Act immediately.

Most dashboards show you metrics. Quorum surfaces findings — with the diagnostic query, the AI explanation, and the safe next action all next to each other.

Observe

Live activity, blockers, slow queries

Active sessions, blocked sessions, root blockers
Long-running queries with wait-event detail
Query fingerprinting + workload trends
Query Store / pg_stat_statements / Performance Schema

Diagnose

Why is this slow / blocking / scanning?

AI explanation of plans & wait events
Missing-index opportunities ranked by impact
Duplicate & overlapping index detection
Scan-heavy table reports

Act

One safe click from the finding

Cancel / terminate with confirmation modal
Generate CREATE INDEX scripts
Open diagnostic in editor
Every action audited & ticket-tagged

Index insights · Missing4 opportunitiesBased on the last 24h of plans

criticalpublic.orders

CREATE INDEX … (status, created_at)

Matches 7 of 12 hot read patterns · 39,210 scans / 24h

Read

23×

Write

+6%

Generate script

highpublic.order_items

CREATE INDEX … (order_id, sku)

2,140 nested-loop joins / hr

Read

8.4×

Write

+4%

Generate script

highpublic.event_outbox

CREATE INDEX … (aggregate_type, published_at) WHERE published_at IS NULL

Partial index opportunity on outbox drain

Read

11×

Write

+2%

Generate script

◇Find the gaps

Find what developers usually miss.

Real-world data goes wrong in quiet ways — orphan child rows, statuses that never advance, duplicates by natural key. Quorum ships a catalog of one-click diagnostics that turn those patterns into a query, a result, and a decision.

Orphaned child rows

124 found in OrderItems

SELECT oi.* FROM order_items oi LEFT JOIN orders o ON o.id = oi.order_id WHERE o.id IS NULL

Stuck workflow status

9 orders in PENDING > 1h

SELECT id, status, age(NOW(), created_at) FROM orders WHERE status = 'PENDING' AND created_at < NOW() - INTERVAL '1 hour'

Duplicate by natural key

27 emails appear twice

SELECT email, COUNT(*) FROM users GROUP BY email HAVING COUNT(*) > 1

Source row missing downstream

2 of 12 orders no shipment

SELECT o.id FROM orders o LEFT JOIN fulfillment.shipments s ON s.order_id = o.id WHERE s.id IS NULL

◆Safety & control

AI assists. You stay in control.

AI suggestions never run themselves on production. Destructive operations sit behind a review wall. Every action is audited, ticket-tagged, and clearly attributed.

No unsafe auto-writes

AI cannot execute UPDATE, DELETE, DROP, ALTER, or batch writes — only prepare them for review.

Preview-before-change

Every proposed write ships with a preview SELECT, an affected-row COUNT, and the proposed statement.

Bounded AI execution

AI-run queries default to LIMIT 100. Configurable per connection. Hardened in the main process.

Explicit cancel / kill

Cancel and terminate-session both require typed confirmation with affected-session count and ticket ref.

WHERE-guard enforcement

UPDATE/DELETE without a WHERE clause is hard-blocked, not warned. Same applies in scripts.

Environment tinting

PROD glows red across the entire workbench. Connection environment determines available actions.

Full audit trail

Every write, kill, and AI-prepared script is logged with user, ticket, environment, and outcome.

Column masking

PII and card numbers stay masked in results, exports, and anything sent to the AI.

◆Open by default

Works with your AI of choice.
Speaks MCP fluently.

Quorum doesn't lock you into one AI vendor — and it doesn't keep your databases trapped inside Quorum. The same safety guardrails apply whether you query from the workbench, Claude Desktop, Cursor, or your own agent.

MQuorum MCP serverthin proxy · main-process safety

Quorum ships a Model Context Protocol server. Point Claude Desktop, Cursor, or any MCP-aware client at it and your existing connections, schemas, and queries become tools the agent can use — without bypassing the write-block, the audit log, or the PROD tinting.

{
  "mcpServers": {
    "quorum": {
      "command": "quorum-mcp",
      "args": ["--connection", "warehouse-prod"]
    }
  }
}

quorum.list_connectionsquorum.run_queryquorum.prepare_writequorum.get_schemaquorum.find_table

◇Configurable models

Bring your own model.

Pick a provider per workspace. Encrypted via OS keychain. The same safety classification runs in the main process regardless of which model generated the suggestion.

Anthropicclaude-haiku-4.5 / claude-sonnet-4.5default · fastest

OpenAIgpt-4o / gpt-4.1 / gpt-4-turbobring API key

Azure OpenAIany deployment · custom endpointenterprise

Ollama (local)llama 3.1 · mistral · qwenfully offline

Local-first by default. Pick Ollama and nothing leaves your machine — no telemetry, no result samples to a vendor, no API roundtrip.

◇

Schema compare

Diff two connections side-by-side. Spot drift between prod, staging, and dev before it hits a release.

◷

Schema history

Snapshots saved per connection. Compare any two points in time; generate the DDL needed to reconcile.

⇄

Migrations & DDL

DDL generator with engine-correct quoting. CSV import, table builder, and parameter-safe templates.

⏱

Scheduling & webhooks

Cron-style scheduled queries; webhook notifications on complete or error; alerts pinned to the dashboard.

◇Multi-database

One workbench for relational and document.

PostgreSQL

9.6 – 16

pg_stat_statements · pg_cancel_backend · plan viewer

SQL Server

2017 – 2022 · Azure

Query Store · sys.dm_exec_requests · DMV diagnostics

MySQL

5.7 – 8 · MariaDB

Performance Schema · KILL QUERY · slow log

◉

MongoDB

4.4 – 7

currentOp · profiler · aggregation pipeline AI

SQLite

Local / embedded

DuckDB

Analytical / local files

Snowflake & BigQuery

Warehouse-aware plans

◆Contact

Ready to see what Quorum could do for your team?

Tell us what you're trying to solve — database investigation, query workflows, observability, or data-quality diagnosis — and we'll get in touch.

A real conversation, not a demo wall

We'd rather hear about the database problem you're trying to solve than walk you through a deck. Bring a real query, a real schema, a real broken workflow — we'll show you how Quorum maps to it.

Hands-on access within a week

If there's a fit, we'll get you onto a private build. You'll connect to your own databases, in your own environment — Quorum is local-first and the binary runs entirely on your machine.

No procurement maze

Pricing is straightforward. Enterprise terms, SSO, and team policies are available — we won't make you chase six approvals to try the product.

Your data stays put

No telemetry by default. Result samples never leave your machine unless you opt in. When AI is involved, the model provider is yours to choose — including fully-offline Ollama.

Your database has answers.
Quorum helps you find them faster.

We're rolling out Quorum to engineering teams a few at a time. Tell us about your databases, your workflow, and what you'd hope to get from a calmer, more intelligent workbench — and we'll get back within two business days.

Contact the team See how it works →

Currently in private beta · macOS · Linux · Windows builds available on request

Understand your database.Investigate issues.Act with confidence.

Not just another database client.

Ask your database better questions.

Trace the problem, not just the syntax.

See what your database is doing.Understand why. Act immediately.

Find what developers usually miss.

AI assists. You stay in control.

Works with your AI of choice.Speaks MCP fluently.

One workbench for relational and document.

Ready to see what Quorum could do for your team?

Your database has answers.Quorum helps you find them faster.

Understand your database.
Investigate issues.
Act with confidence.

See what your database is doing.
Understand why. Act immediately.

Works with your AI of choice.
Speaks MCP fluently.

Your database has answers.
Quorum helps you find them faster.