Futurelab enterprise products ship as a working starting point (decision engines, knowledge hubs, assistants and workflow automation), which embedded engineers then adapt to your data sources, permissions and workflow rules before launch under your brand.
They are AI tools built for internal team use (decision engines, knowledge hubs, virtual assistants and workflow automation) that can be deployed under your own brand. They ship as a working starting point that forward deployed engineers then fit to your data and processes.
White-label means the product is deployed under your brand, on your domain, for your users. Futurelab supplies and maintains the underlying system; your teams and customers see your identity.
Every product is expected to be customised. The base system handles the common patterns, and the deployment engagement adapts data sources, permissions, terminology and workflow rules to the way your organisation actually works.
Pricing depends on deployment scope, the number of users, and how much integration the environment requires. Contact hello@futurelabstudios.com with your use case for a scoped quote.
AI adoption is the work of getting AI used in daily operations, as distinct from buying AI tools. It covers choosing workflows, redesigning them, building what is needed, and training the people who will run them. Organisations that treat it as a procurement exercise typically end up with licences and no change in how work is done.
The reliable benefit is time returned on repetitive work, which compounds because it applies every time the process runs. Secondary benefits, such as better consistency, faster response and fewer handoffs, follow from the same change. Benefits that depend on judgement improving are much harder to evidence and should be treated sceptically when promised.
Typically discovery and workflow selection, data access and security scoping, the build, evaluation, rollout and training, then handover. The parts most often underspecified are security scoping and handover. Agreeing both in writing before the build starts is the single most effective way to keep an enterprise engagement from stalling.
A single well-scoped workflow is usually a matter of weeks; programmes spanning several departments run considerably longer, mostly because of data access and approvals rather than engineering. Sequencing one workflow at a time gives you a working system early and a real basis for deciding whether to extend.