BeforeQuery vs OpenAI Assistants API
OpenAI Assistants API is a framework for building custom assistants. BeforeQuery is a packaged knowledge assistant — retrieval, chunking, connectors, widget, bots, evals, and analytics are shipped, not built. This comparison is about product vs framework, and the total cost of ownership.
Feature comparison
Comparison based on OpenAI Assistants API documentation and Platform pricing pages.
Where BeforeQuery focuses differently
A product, not a framework
The Assistants API is a set of building blocks. Turning them into a production assistant means building the ingest pipeline, the chunker, retrieval quality, the eval harness, the widget, the Slack/Discord/Teams bots, the analytics dashboard, and the ops. BeforeQuery ships all of that. The build-vs-buy question isn't 'can we build this?' — it's 'is this a differentiator worth 3–6 months of engineering per year?'
Retrieval tuned for docs, out of the box
File Search uses vector search on uploaded files. Docs assistants need more: HTML→markdown normalisation that strips nav and boilerplate, code-block extraction, heading-aware chunking, PDF structure inference, hybrid + reranking, and abstention. Those are the pieces most build-your-own projects underinvest in and then discover after launch.
The connectors are the moat
Building one connector (Zendesk) with correct pagination, incremental sync, permission handling, and re-index-on-webhook is a two-week engineering project. Doing 18 of them, keeping each up-to-date as vendor APIs change, is a full-time job. BeforeQuery ships and maintains all of them.
You own the answers, not the infrastructure
Bring-your-own-model (Enterprise) means BeforeQuery calls OpenAI on your account with your key. You keep control over the model and the bill; you skip owning the platform.
Frequently asked questions
When would I still build on OpenAI Assistants API instead?
If your assistant needs highly custom logic that isn't docs Q&A — for example, a therapy chatbot, a coding agent with custom tools, or an on-brand consumer character — the flexibility of a framework is the right choice. For docs and support Q&A, the packaged product wins on time-to-value and ongoing ownership.
Do I lose flexibility by using BeforeQuery?
For flow-based bots, yes. For docs/support Q&A, no — SDKs (web, React, Widget, Agents), an open REST + WebSocket API, an MCP server, and an A2A endpoint give you enough surface to build custom experiences on top of the packaged assistant.
Can I bring my own OpenAI key?
Yes on Enterprise. BYOK routes traffic through your OpenAI account and your usage bill, and honors your data-processing agreement with OpenAI. You keep the model choice and the invoice; BeforeQuery is the platform.
How does total cost compare?
BeforeQuery is flat monthly: Free / $99 Pro / Enterprise custom. Building on the Assistants API means OpenAI usage costs (which you'd have with BeforeQuery on BYOK too) plus your engineering time (usually 3–6 months for a production docs assistant with widget + bots + evals) plus ongoing maintenance (connectors break when vendors change APIs).
How is retrieval quality measured on the build-your-own path?
You write an eval harness. BeforeQuery ships LLM-as-judge groundedness + citation scoring with weekly trends — the piece most in-house builds skip and then discover after a bad release.
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