We need an internal knowledge bot for our 12-person team. Docs are in Notion, some in Google Drive. Goal: quick answers on processes, past project details, etc.
Tested both SuperAGI (self-hosted open source) and ChatGPT's GPTs (paid team plan). Results after 2 weeks:
**SuperAGI:**
- More control. Connected directly to our Notion API.
- Ran into constant tuning issues. Agent would get stuck in loops.
- Dev time was huge. My CTO spent days on configs. Not worth the hourly cost for us.
**ChatGPT GPTs:**
- Dead simple. Uploaded some docs, added the Notion share link.
- Answers are faster for the team, but it hallucinates more than we'd like.
- Recurring cost is predictable, but it's another subscription.
For a small bootstrapped team, GPTs win on time-to-value. But the inaccuracies are a real problem. We're sticking with it for now, but I'm watching open source alternatives.
Anyone else run both? Did you find a way to reduce the hallucinations with GPTs?
I'm a security lead at a 40-person fintech. Our whole ops knowledge base lives in Confluence, and we run a GPT-4 powered bot for internal Q&A, built on a self-hosted LangChain setup.
**Core comparison for SuperAGI vs ChatGPT GPTs:**
1. **Total cost of ownership:** ChatGPT Teams is $25/user/month flat. SuperAGI's open source is "free", but you pay in devops. At my last shop, we spent 15-20 engineering hours per month on tuning and infrastructure, which at bootstrapped rates is a $1500-2000 monthly tax.
2. **Hallucination control:** GPTs have none. You get the vanilla GPT-4 behavior. With a self-hosted framework like SuperAGI, you can enforce strict grounding. We forced a "retrieve-then-answer" chain and dropped our hallucination rate from ~15% to under 5%, but it required a senior dev for a week.
3. **Compliance & audit trail:** GPTs give you a chat history, but you can't log raw token usage per document or see the exact source chunk used for an answer. SuperAGI let us pipe every query and its document sources to our SIEM, which is non-negotiable for SOC 2 audits.
4. **Breakage profile:** GPTs break silently with hallucinations. SuperAGI breaks loudly with agent loops or API timeouts. The latter is easier to alert on but requires someone on call who can debug a Python agent.
My pick is neither for your size. For a 12-person team that's already feeling the hallucination pain, I'd recommend a middle-ground like **CustomGPT** or **Claude for Teams**. They're built for this, have better citation, and cost about the same as ChatGPT Teams. If you must pick between the two, use GPTs only for low-stakes, general process questions. To make a clean call, tell us your budget for initial setup and how many answers per day would be catastrophic if they were wrong.
Trust but verify