Connect your data, agents, and tools. Add your team, and start interacting. PromptQL captures shared context as your team works, enabling it to operate like a trusted teammate you rely on.
Build together.
Connect to any remote computer or coding agent. Your whole team is in the same thread. Someone reports a bug, PromptQL already knows the product context, Codex investigates and ships the fix. Everyone sees what happened.
CodexClaude CodeCustom agents+ more
TanmaiEng
📎 screenshot-ios-wiki-bug.png
Mobile wiki view is broken. Button not responding sometimes? @PromptQL delegate to Codex, find root cause and open a PR.
PromptQL
▸ Delegating to Codex
Passing screenshot and wiki context: v3-console repo, Next.js App Router, iOS Safari click handler gotchas...
RikinEng
Check if it's the same issue from last week. We had a z-index problem with the overlay
PromptQL
Good lead. Codex found it. WikiLearningOverlay z-index: 10, ActionButton z-index: 5. Button renders UNDER the overlay.
✓ Fix pushed. PR #3505 opened: z-index fix + test case
ManushiEng
Tested on staging, works. Merging. ✓
👥 4⏱️ Bug → PR → Merged in 14 min
Solve together.
Connect to any database or SaaS service. An alert fires, someone checks it, someone else connects it to a recent deploy. PromptQL pulls the metrics, correlates the data, and the whole team debugs together in one thread. No war room, no Zoom call.
incident.ioDatadogKubernetesSnowflake+ more
ShahidhPlatform
@PromptQL check the latest alert from incident.io. I see OOMKilled. Which pod, what data plane?
PromptQL
Critical alert: OOMKilled on 3 api-server pods.
| Pod | Memory | Restarts | Last |
|---|---|---|---|
| api-server-7b4 | 3.8 GB | 4 | 2:38 PM |
| api-server-2c9 | 3.6 GB | 3 | 2:35 PM |
| api-server-1a3 | 3.7 GB | 5 | 2:40 PM |
TomaszPlatform
We deployed the new batch processor at 2:30. Could be related.
PromptQL
Checking. Batch processor memory grew 3x after deploy. Loading full dataset into memory instead of streaming.
| Process | Pre | Post | Change |
|---|---|---|---|
| batch-worker | 1.1 GB | 3.4 GB | +209% |
| api-server | 2.1 GB | 3.7 GB | +76% |
AravindPlatform
Rolling back batch processor. @PromptQL monitor recovery.
PromptQL
✓ Memory normalized. All pods stable.
👥 11⏱️ Alert → Root cause → Fixed in 11 min
Sell together.
Connect to Salesforce, Gmail, LinkedIn. All your personal and shared services. Shared context means no more DMs, no more "does anyone know anything about this account?" Everyone talks to PromptQL, adds what they know, and the output keeps getting better.
SalesforceLinkedInGmailGoogle Calendar+ more
JakobSales
Discovery call with Walmart in 2 hours. @PromptQL get me everything on Ra*** G*** and their data stack.
PromptQL
Here's your briefing:
Ra*** G***, Sr. Director, Customer Data & AI
Reports to: VP of Enterprise Data · 8 yrs at Walmart, prev. Target
Pain signal: "semantic layer maintenance" (LinkedIn)
Stack: Snowflake, dbt, Tableau
Company context
Data & analytics investment up 23% · New Chief AI Officer (Jan 2026) · Approached by Databricks last month
MichaelSales
@PromptQL check if we have notes from AWS re:Invent. I talked to Ra*** there, he said they spend 40% of data eng time on dashboards.
PromptQL
Found your re:Invent notes. Dashboard maintenance burden, Tableau licensing frustration. Added to briefing + pulled our ROI case study (Target saw 60% reduction).
AdamGTM
@PromptQL their CFO just changed. Ex-Amazon, obsessed with unit economics. Reframe around cost, not features.
PromptQL
Done. Reframed around cost/efficiency, added unit economics comparison.
📋 FINAL BRIEFING: walmart_discovery_brief.pdf
Jakob
Perfect. Walking in prepared.
👥 5🎯 Request → Team input → Brief: 19 min
BULLETPROOF SECURITY
All this works because we have bulletproof security.
Permissions and access control sophisticated enough for the Fortune 100. Complex controls, heterogeneous data, full auditability. But easy enough to keep up with the pace of change of an AI-native team.
Easy authorization
Simple, intuitive access controls. Inherit and enforce policies from existing systems like SSO and IAM.
AI-guided access
PromptQL suggests what access to grant based on roles and resource type. Easy onboarding for new users and sources.
Permission-aware execution
Every request evaluated in real time. Queries only return what the requester is allowed to see.
User and agent directory
Manage identities for humans and AI agents in one place. Consistent policies across all interactions.
Full auditability
Every action is logged, traceable, and explainable. See who accessed what, ensuring accountability and compliance.
Scalable governance
Extend access policies as you add new data sources, users, and AI agents. No rewriting rules or introducing risk.
The vibe shift
Our team moved off Slack entirely.
We're not saying you should. But we did. And this is what it actually feels like.