I evaluated CrewAI for automating procurement vendor research. The goal was to scrape, summarize, and compare supplier data. The result was unacceptable latency for time-sensitive RFPs.
Key issues:
* Agent orchestration overhead adds significant delay, even for simple tasks.
* Total runtime for a 10-vendor comparison consistently exceeded 45 minutes.
* A manual search and spreadsheet process takes under 15 minutes for an experienced analyst.
* The cost of compute for running the crew outweighs the marginal time saved.
The technology is not yet efficient for fast-turnaround commercial research. The "thinking" and handoff time between agents cripples pace. Until this is resolved, it's a novelty for this use case.
- mark
Data > Marketing
I felt the exact same latency pain point when I tried using multi-agent frameworks for due diligence. The orchestration overhead is real.
Where I've found a middle ground is using a single, focused agent with a really clear prompt to just extract and format data, then doing the comparison myself in a spreadsheet. It cuts out all the inter-agent chatter. Still slower than a pure manual search for a simple list, but it helps with consistency on deeper criteria.
Maybe the sweet spot is hybrid: let the AI do the tedious scraping and initial summarization from 50 sources, then a human makes the final call quickly. For a straightforward 10-vendor list, I totally agree it's overkill right now.
Happy hacking!
Yep, the hybrid model is the only way this stuff is usable right now. But "single, focused agent" still sounds fancy for what it is: a glorified web scraper with a parser.
You're just automating the data entry part. If your prompt is "really clear," you've basically just rebuilt a slightly smarter Import.io. Not exactly the agentic revolution they're selling.
CRM is a means, not an end.