CustomGPT for customer-facing chatbots.docAnalyzer for the work behind them.
CustomGPT deploys a chatbot trained on your docs, fast. docAnalyzer ships chatbots too, plus the practitioner workflows, batch operations, and Co-work canvas that produce the docs the chatbot is built on. One tool for both audiences.
No credit card. Both audiences covered in one workspace.
Customer-facing chatbots are one piece of the document problem.
CustomGPT is built for one shape: train an outbound chatbot on your help center and support docs, embed it on your site, let customers ask questions. That works, and docAnalyzer does it too.
What CustomGPT doesn't address is the inbound side: your team running batch analysis across vendor contracts, drafting new policies in a canvas editor, extracting structured fields from RFP responses. The work the chatbot is built on. If you only need the customer-facing chatbot, CustomGPT is the simpler tool. If you need both, the integrated workspace is.
CustomGPT
docAnalyzer
Customer-facing chatbots
The core use case. Easy widget embedding, branded UI, trained on your docs.
Embed branded Chatbots on your site, backed by a label of documents. Parity for the core chatbot use case.
Practitioner workflows
Not the use case. CustomGPT is built for outbound chatbots, not inbound team work.
Three chat modes (Ask, Focus, Co-work) for team document work: different shape from the customer-facing chatbot.
Batch operations
Not supported. Conversational only.
Five workflows (Summarizer, Data Extractor, Individual, Blueprint, Humanizer) run across every source in a dataset.
Co-work (drafting alongside AI)
Not supported.
Canvas editor where the AI drafts new policies, onboarding docs, contracts alongside you, with citations attached.
Citation discipline (for team use)
Citation infrastructure scoped to customer chat answers.
Cited claims are clickable references that open the source at the exact page or section: the same discipline whether the asker is a customer or your team.
In their own words
“I use docAnalyzer every damn day, to compare résumés to job postings, review contracts, ask questions about terms of service, summarize, and a lot more.”
Aaron Freed, CEO recruitingguy.com (Product Hunt)
What CustomGPT users push on hardest.
We want a customer-facing chatbot, not a research workspace.
docAnalyzer ships embeddable Chatbots too: branded, label-backed, with the same widget embedding pattern. The workspace exists in addition. If you only ever need the chatbot, the workspace is just there if you want it.
CustomGPT is simpler to deploy.
For a one-time chatbot deployment, possibly. If the chatbot is one of several things you want from your AI-for-docs tool (and most teams have a few) the integrated workspace removes the tool-stack tax.
Our customers ask basic questions. We don't need the heavy machinery.
For the chatbot side, you don't. docAnalyzer's chatbot doesn't expose the workspace heavy machinery to your end users: they get the clean question-and-answer experience CustomGPT also offers. The heavy machinery is for your team.
CustomGPT is priced for mid-market chatbot deployment. We don't want a heavier bill for a tool that also has to cover team work.
docAnalyzer's tiers are structured for both audiences in one workspace: the chatbot use case CustomGPT prices for, plus the practitioner workflows it doesn't, without paying for a second tool. Compare on /pricing.