Construction and infrastructure
Case studies
We scale AI in mid-sized and large organisations.
Examples of agents and AI adoption: the starting point, how the solution works and the value for the team.
We measure value on three levels:
- Time savedLess repetitive work. More time for decisions, relationships and tasks that need experience.
- Sales and revenueMore efficient quoting and customer service, and new services built on data.
- New possibilitiesAnalysis and actions previously held back by limited time, people or access to knowledge.
Scope
Case studies: 10
From single prompts to AI in the company's everyday work
Manufacturing company0 → 47solutions built by employees and used in their work, across 11 areas of the company (another 4 in pilot)47%of respondents built their own project, skill or automation that they use regularly (survey 05.2026, 51 people)Since December 2025 the company has moved from isolated experiments to AI in everyday work. In a May 2026 survey (51 people, mostly ambassadors), 88% used Claude daily or several times a week, and 47% had built their own project, skill or automation that they use regularly.See the case studyA quote ready for the client, days ahead of the competition
Manufacturing company7 days → 1 dayresponse time for enquiries handled by the agentFrom a niche curiosity to everyday work
Pharmaceutical company10% → 87%adoption of the internal AI assistant30-40 → 160+daily active usersFrom knowledge scattered across many spreadsheets to one selection tool
Manufacturing companyup to 1 h → <10 minpilot target: product selection timeapprox. 99%of selection formulas from the ERP imported automaticallyFrom a few AI enthusiasts to teams building prototypes
B2B distribution company21AI prototypes built by employees7directors' prototypes shown on Demo DayQuestions in Teams that find their answers in company data
Manufacturing company14 weeksfrom start to working in Teams4 sourcesof knowledge in one conversation: FAQ, procedures, products, peopleFinancial statements and reports without manual retyping
A financial company80-90%*approx. 3 min instead of 15-30 min of retypingmin. 90%*of documents processed automatically, the rest go to an analystAI that keeps data inside the company
A financial company100%*of production processing on the company's servers2*first processes being prepared to run on this serverFrom individual employees' grassroots attempts to a shared list of priorities
FMCG manufacturerapprox. 1,800*employees covered by the AI Act training plan60-70*board members and managers in the programmeAI functionality in a grant-matching platform
Work in progress. We will share the details on completion.
Work in progress. These are results verified at the test stage or the targets we are aiming for. We will confirm them on completion.
Most of our projects are covered by NDAs, so we only share part of them, without client names or details, as inspiration. We are happy to tell you more about our experience in a conversation.
No published example matches this selection yet.
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Explore the solutionTestimonials
“We greatly value the WeAreFuture team’s ability to work within everyday system constraints, their flexibility in quickly finding effective solutions and their focus on measurable, functional goals. Our cooperation can be summed up in one sentence: if you want to succeed in today’s digital reality, this is exactly how to work together.”
Grzegorz KawalerCIO, Smay Ventilation Systems
“I value their practical approach and broad expertise in connecting AI with business reality.”
Kiril MarinovManaging Director, Henkel Consumer Brands
“I value the team’s depth of expertise, practical approach and commitment to developing the skills of leaders and teams.”
Magda Gajownik de VriesInnovation Development Department, Polish Development Fund (PFR)
“The meeting helped us look at AI in a structured way and identify the specific areas with the greatest business potential.”
Grzegorz DróżdżHead of Mkt & Comms, Investors TFILet’s talk about the work you want to improve.
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