Comparison

Building your own RAG assistant vs buying one

Building the demo is genuinely easy now. That is exactly what makes this decision harder than it looks.

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The prototype is not the product

A retrieval prototype over your docs is a weekend. Everything after that — crawling, re-indexing, refusal tuning, escalation, rate limiting, abuse control, multi-tenancy, analytics — is the part that takes a year and never appears in the estimate.

  • A convincing demo that never reaches production
  • Estimates covering retrieval and nothing operational
  • No plan for keeping the index current
  • Cost controls left until after the first surprising bill

What building genuinely gives you

Control. If your retrieval needs are unusual — proprietary ranking, domain-specific chunking, data that cannot leave your infrastructure — building is the only way to get exactly that, and no product will fit a genuinely unusual requirement.

Unusual retrieval needs

Domain-specific ranking or chunking logic.

Data residency

Where content genuinely cannot leave your systems.

Deep integration

Retrieval fused with your own product surfaces.

What is easy to underestimate

Crawling and scheduled re-indexing. Refusal behaviour that holds under adversarial phrasing. Escalation with transcripts. Rate limiting and spend caps. Conversation logging and analytics. Multi-tenancy if you serve clients. Each is small; together they are the product.

An honest way to decide

If retrieval quality is your competitive advantage, build it. If it is a support cost centre, the engineering time is almost certainly worth more spent on whatever your product actually does.

Common questions

We already have engineers — should we build?
Having the capability is not the same as it being the best use of it. The question is whether this is the highest-value thing those engineers could ship this quarter, and for most teams it is not.
What is the most underestimated part?
Keeping the index current, and refusal behaviour that survives adversarial phrasing. Both are easy to get 80% right in a prototype and genuinely difficult to make dependable.

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