Comparison
Build vs. buy: customising an enterprise AI platform
Building an enterprise AI platform in-house gives you total control but demands months of engineering and ongoing maintenance, while buying a platform delivers value in weeks. The real decision is rarely binary: the strongest option is often a customisable platform that you can self-host and extend, capturing buy-side speed with build-level control.
The trade-off
| Dimension | Build in-house | Customisable platform |
|---|---|---|
| Time to value | Months+ | Weeks |
| Multi-model support | Build & maintain each | Included |
| Security & guardrails | Build yourself | Built in |
| Self-hosting & data residency | Possible, you own it all | Supported |
| Custom integrations & agents | Full effort | Extend the platform |
| Maintenance burden | High | Shared with vendor |
When to build
- Your AI workflow is a core, differentiating part of your product.
- You have dedicated engineering capacity to maintain it long term.
- Requirements are highly specific and unlikely to be met off the shelf.
- You need to own every layer of the stack for regulatory or IP reasons.
When to buy (and customise)
- You want value in weeks rather than months.
- You need multi-model support, security, and guardrails out of the box.
- You'd rather share the maintenance burden with a vendor.
- You still need room to extend with your own integrations and agents.
A third option: customise a platform
ChatLite is designed for teams that don't want to choose between speed and control. It can be self-hosted in your own environment for full data residency, and it's built to be customised to your organisation's needs.
Beyond configuration, ChatLite can be custom-built with the integrations, data feeds, and custom agents your workflows depend on. You get the fast time to value of buying, paired with the deep control you'd normally only get from building it all yourself.
Learn more about how teams deploy and extend it on the enterprise page.