How We Used Retool to Build an Internal AI Copilot in 1 Week

Duy Vu
August 8, 2025
10 mins read
How We Used Retool to Build an Internal AI Copilot in 1 Week

In the fast-moving world of internal tools, speed isn't just nice to have — it's everything. At Retoolers, we help businesses streamline operations and move faster. This time, we turned the lens on ourselves and asked: “What if we could supercharge our own workflows with an AI copilot?”

Spoiler: we did. And we built it in just one week — using Retool, OpenAI’s GPT, and a clean UI that feels like magic (but isn’t).

The Problem: Too Many Internal Questions, Too Little Time

Our team was drowning in repetitive questions:

  • “What’s the status of Project X?”
  • “Who’s the developer on Y?”
  • “Where’s the latest client dashboard file?”
  • “Can I get the changelog for our last Retool push?”

We needed a solution that could:

  • Pull info from our internal tools
  • Understand natural language
  • Give instant answers
  • Be easy to maintain

The obvious choice: build an AI copilot inside Retool.

Step 1: Mapping It Out in Figma

Like every solid product build, it started with design.

We mocked up:

  • A simple chat interface
  • Suggested prompts
  • Context tags for different types of queries
  • Tabs for “General Info”, “Project Status”, and “Retool Logs”

We wanted it to feel like Notion meets ChatGPT — but 100% internal and powered by our own data.

Step 2: Building It in Retool

Retool gave us the perfect foundation. In just a few hours, we:

  • Created a chat UI using Retool’s container + text input blocks
  • Hooked up API connectors to OpenAI
  • Integrated our internal PostgreSQL database
  • Added logic to show different responses based on query intent

We used:

  • OpenAI GPT-4 for language generation
  • SQL queries to pull internal data (status updates, owner, etc.)
  • Retool Workflows to clean up messy inputs and parse intent
Internal link idea: Curious how we build real AI apps in Retool? See our AI Content Editor use case.

Step 3: Fine-Tuning the Output

GPT was powerful — but also too chatty at first.

We:

  • Tuned prompt instructions to return concise results
  • Added fallback messages for vague inputs
  • Created a quick feedback button: "Was this helpful?"

To polish the UI:

  • We used the Lovable theme for softer 3D-like input blocks
  • Added color coding for different types of replies
  • Used a sticky suggestion bar to guide first-time users

Results: What We Got in 1 Week

✅ Internal questions answered in seconds

✅ Reduced interruptions in Slack

✅ Gained full visibility into project info

✅ Saved dev time by 30%

✅ Inspired 3 more AI tools we’re now testing

And best of all — we can duplicate this for clients.

Why This Matters for You

If you’re managing a growing team and drowning in questions, delays, or tool overload — this is your wake-up call.

You don’t need to wait for a massive platform. You just need:

  • Retool
  • A clear workflow
  • A week of focused building

And maybe a team like Retoolers to guide you.

Want us to build your AI Copilot? Get a quote

Duy Vu
Internal Tool Designer

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