The build-versus-buy question for LLM features is a variant of a decision enterprises have made for decades, with one twist: the "build" option has become dramatically cheaper. A working Claude integration is a few dozen lines of Python against a well-documented API, not a machine-learning research project. That does not make building right for every case — a vendor product bundles years of workflow design, UI, and edge-case handling you would otherwise rediscover the hard way. The useful move is to stop treating this as one decision and start scoring each use case on a few concrete factors.
What "build" actually means now
Building does not mean training a model. It means calling Claude through a platform you already operate — Bedrock, Vertex AI, Foundry, or Claude Platform on AWS — with your own prompts, your own data, and your own integration into internal systems. The heavy lifting (the model itself, scaling, availability) is the platform's job. Your team's job is the part no vendor can do: encoding your business rules, connecting your data sources, and designing where humans review the output. For a team with ordinary software engineering skills, that is weeks of work for a first version, not quarters — the one-week proof of concept plan exists precisely because the entry cost is that low.
When buying wins
Buy when the use case is generic and the workflow is the product. Meeting transcription, generic writing assistance, coding assistants, CRM-embedded drafting — these are problems vendors have refined across many customers, and your requirements probably are not special. Buy when the AI feature lives inside a system you already license and the vendor's integration is deeper than anything you could bolt on from outside. Buy when you have no engineering capacity to own another production system — a built integration is not a one-time cost; someone must maintain prompts, monitor quality, and handle upgrades for as long as it runs. And buy when time-to-value dominates: a credible vendor tool deployed this quarter usually beats a custom build deployed next year.
When building wins
Build when the value comes from your data and your process — a claims-summarization flow shaped by your policies, an internal assistant grounded in your documentation, a document pipeline tuned to your contract formats. Vendor products flatten exactly the specificity that makes these valuable. Build when data governance is strict: an integration you run inside your own cloud boundary keeps traffic within the identity, logging, and network controls your security team already audits, and largely inherits your cloud provider's compliance posture — confirm specifics with your provider. Build when the economics matter at scale: with a vendor product you pay per seat or per unit for the whole package; with your own integration you pay per token and control the biggest cost levers yourself, like routing routine work to Haiku 4.5 and reserving Opus 4.8 for hard cases. And build when the capability is strategic — if this workflow is part of how you compete, renting the generic version of it is a strange choice.
The hybrid most enterprises land on
In practice this is a portfolio decision, not a single verdict. Most enterprises end up buying commodity productivity tools for the workforce while building two or three high-value integrations where their data and process are the moat. If you go that route, two habits keep the portfolio manageable. First, route your built integrations through one internal gateway so authentication, logging, and cost attribution are consistent — the internal AI gateway pattern covers this. Second, ask vendors the same questions you would answer for your own build: which model and version is inside, where does inference run, what data is retained, and can you export your configuration if you leave. A vendor who cannot answer those is asking you to buy a black box.
Whichever way a given use case goes, run a small evaluation before committing — the same eval-set discipline applies to a vendor's output as to your own prompts. "Impressive in the demo" is not a procurement criterion.
Where to go next
If you lean toward building, the one-week proof of concept plan shows how cheaply you can validate the idea, and the team skills article covers who you need to run it. The quickstart is the fastest way to see what "build" feels like firsthand.